This directory contains the tasks that are part of this benchmark.
| Name | Summary | Category | Domain | Input Language | Output Language |
|---|---|---|---|---|---|
task001_quoref_question_generation |
Writing questions that require tracking entity references. | Question Generation | Wikipedia | English | English |
task002_quoref_answer_generation |
Answering questions that require tracking entity references. | Question Answering | Wikipedia | English | English |
task003_mctaco_question_generation_event_duration |
Writing questions that involve commonsense understanding of "event duration". | Question Generation | News, Wikipedia, Law, Justice, History, History -> 9/11 Reports, Anthropology, School Science Textbooks, Fiction | English | English |
task004_mctaco_answer_generation_event_duration |
Answering questions that involve commonsense understanding of "event duration". | Question Answering | News, Wikipedia, Law, Justice, History, History -> 9/11 Reports, Anthropology, School Science Textbooks, Fiction | English | English |
task005_mctaco_wrong_answer_generation_event_duration |
Writing an implausible answer to the given "event duration" question. | Wrong Candidate Generation | News, Wikipedia, Law, Justice, History, History -> 9/11 Reports, Anthropology, School Science Textbooks, Fiction | English | English |
task006_mctaco_question_generation_transient_stationary |
Writing questions that involve commonsense understanding of "transient vs. stationary" events. | Question Generation | News, Wikipedia, Law, Justice, History, History -> 9/11 Reports, Anthropology, School Science Textbooks, Fiction | English | English |
task007_mctaco_answer_generation_transient_stationary |
Answering questions that involve commonsense understanding of "transient vs. stationary" events. | Question Answering | News, Wikipedia, Law, Justice, History, History -> 9/11 Reports, Anthropology, School Science Textbooks, Fiction | English | English |
task008_mctaco_wrong_answer_generation_transient_stationary |
Writing an implausible answer to a "transient v. stationary" question. | Wrong Candidate Generation | News, Wikipedia, Law, Justice, History, History -> 9/11 Reports, Anthropology, School Science Textbooks, Fiction | English | English |
task009_mctaco_question_generation_event_ordering |
Writing questions that involve commonsense understanding of "event ordering" of events. | Question Generation | News, Wikipedia, Law, Justice, History, History -> 9/11 Reports, Anthropology, School Science Textbooks, Fiction | English | English |
task010_mctaco_answer_generation_event_ordering |
Answering questions that involve commonsense understanding of "event ordering". | Question Answering | News, Wikipedia, Law, Justice, History, History -> 9/11 Reports, Anthropology, School Science Textbooks, Fiction | English | English |
task011_mctaco_wrong_answer_generation_event_ordering |
Writing an implausible answers to the given "event ordering" question. | Wrong Candidate Generation | News, Wikipedia, Law, Justice, History, History -> 9/11 Reports, Anthropology, School Science Textbooks, Fiction | English | English |
task012_mctaco_question_generation_absolute_timepoint |
Writing questions that involve commonsense understanding of when events typically happen. | Question Generation | News, Wikipedia, Law, Justice, History, History -> 9/11 Reports, Anthropology, School Science Textbooks, Fiction | English | English |
task013_mctaco_answer_generation_absolute_timepoint |
Answering questions that involve commonsense understanding of "absolute timepoint" of events. | Question Answering | News, Wikipedia, Law, Justice, History, History -> 9/11 Reports, Anthropology, School Science Textbooks, Fiction | English | English |
task014_mctaco_wrong_answer_generation_absolute_timepoint |
Writing an implausible answer to the provided "absolute timepoint" question. | Wrong Candidate Generation | News, Wikipedia, Law, Justice, History, History -> 9/11 Reports, Anthropology, School Science Textbooks, Fiction | English | English |
task015_mctaco_question_generation_frequency |
Writing questions that involve commonsense understanding of events' "frequencies". | Question Generation | News, Wikipedia, Law, Justice, History, History -> 9/11 Reports, Anthropology, School Science Textbooks, Fiction | English | English |
task016_mctaco_answer_generation_frequency |
Answering questions that involve commonsense understanding of event "frequency". | Question Answering | News, Wikipedia, Law, Justice, History, History -> 9/11 Reports, Anthropology, School Science Textbooks, Fiction | English | English |
task017_mctaco_wrong_answer_generation_frequency |
Writing an implausible answer to the given event "frequency" question. | Wrong Candidate Generation | News, Wikipedia, Law, Justice, History, History -> 9/11 Reports, Anthropology, School Science Textbooks, Fiction | English | English |
task018_mctaco_temporal_reasoning_presence |
Checking the presence of temporal reasoning in a question. | Question Understanding | News, Wikipedia, Law, Justice, History, History -> 9/11 Reports, Anthropology, School Science Textbooks, Fiction | English | English |
task019_mctaco_temporal_reasoning_category |
Verifying the temporal reasoning category of a given question. | Question Understanding | News, Wikipedia, Law, Justice, History, History -> 9/11 Reports, Anthropology, School Science Textbooks, Fiction | English | English |
task020_mctaco_span_based_question |
Checking whether the given sentence contains answer to the given question. | Answerability Classification | News, Wikipedia, Law, Justice, History, History -> 9/11 Reports, Anthropology, School Science Textbooks, Fiction | English | English |
task021_mctaco_grammatical_logical |
Checking grammatical and logical correctness of a question. | Text Quality Evaluation | News, Wikipedia, Law, Justice, History, History -> 9/11 Reports, Anthropology, School Science Textbooks, Fiction | English | English |
task022_cosmosqa_passage_inappropriate_binary |
Identifying inappropriate content in context sentences. | Toxic Language Detection | Personal Narratives | English | English |
task023_cosmosqa_question_generation |
Craft one question such that it requires commonsense to be answered. | Question Generation | Personal Narratives | English | English |
task024_cosmosqa_answer_generation |
Answering commonsense questions. | Question Answering | Personal Narratives | English | English |
task025_cosmosqa_incorrect_answer_generation |
Writing incorrect answers options for a commonsense question. | Wrong Candidate Generation | Personal Narratives | English | English |
task026_drop_question_generation |
Creating complex reasoning questions based on a passage. | Question Generation | Sports, Sports -> NFL, Wikipedia, History | English | English |
task027_drop_answer_type_generation |
Finding the answer type of a reasoning question. | Question Understanding | Sports, Sports -> NFL, Wikipedia, History | English | English |
task028_drop_answer_generation |
Answering a complex reasoning question based on a passage. | Question Answering | Sports, Sports -> NFL, Wikipedia, History | English | English |
task029_winogrande_full_object |
Creating a pair of fill in the blank question-answer pairs on objects. | Question Generation | Commonsense -> Concepts and Relations -> Social Commonsense, Commonsense -> Concepts and Relations -> Physical Commonsense | English | English |
task030_winogrande_full_person |
Creating a pair of fill in the blank questions on persons. | Question Generation | Commonsense -> Concepts and Relations -> Social Commonsense, Commonsense -> Concepts and Relations -> Physical Commonsense | English | English |
task031_winogrande_question_generation_object |
Writing a fill in the blank question on objects. | Question Generation | Commonsense -> Concepts and Relations -> Social Commonsense, Commonsense -> Concepts and Relations -> Physical Commonsense | English | English |
task032_winogrande_question_generation_person |
Writing a fill in the blank question on persons. | Question Generation | Commonsense -> Concepts and Relations -> Social Commonsense, Commonsense -> Concepts and Relations -> Physical Commonsense | English | English |
task033_winogrande_answer_generation |
Answering a fill in the blank question on objects. | Coreference Resolution | Commonsense -> Concepts and Relations -> Social Commonsense, Commonsense -> Concepts and Relations -> Physical Commonsense | English | English |
task034_winogrande_question_modification_object |
Modifying a fill in the blank question on objects. | Question Rewriting | Commonsense -> Concepts and Relations -> Social Commonsense, Commonsense -> Concepts and Relations -> Physical Commonsense | English | English |
task035_winogrande_question_modification_person |
Modifying a fill in the blank question on persons. | Question Rewriting | Commonsense -> Concepts and Relations -> Social Commonsense, Commonsense -> Concepts and Relations -> Physical Commonsense | English | English |
task036_qasc_topic_word_to_generate_related_fact |
Writing a topic word related to a given fact. | Keyword Tagging | Natural Science | English | English |
task037_qasc_generate_related_fact |
Constructing a related fact based on a given topic word. | Sentence Composition | Natural Science | English | English |
task038_qasc_combined_fact |
Combining two facts. | Sentence Composition | Natural Science | English | English |
task039_qasc_find_overlapping_words |
Finding overlapping words between two sentences. | Overlap Extraction | Natural Science | English | English |
task040_qasc_question_generation |
Creating a question based on a given sentence. | Question Generation | Natural Science | English | English |
task041_qasc_answer_generation |
Writing correct answer to a given question based on a given sentence. | Question Answering | Natural Science | English | English |
task042_qasc_incorrect_option_generation |
Writing incorrect answers to a given question based on a given sentence. | Wrong Candidate Generation | Natural Science | English | English |
task043_essential_terms_answering_incomplete_questions |
Answering incomplete questions. | Misc. | Natural Science | English | English |
task044_essential_terms_identifying_essential_words |
Identifying words or phrases of the question essential for choosing the correct answer. | Question Understanding | Natural Science | English | English |
task045_miscellaneous_sentence_paraphrasing |
Generating sentence paraphrases. | Paraphrasing | Natural Science | English | English |
task046_miscellaneous_question_typing |
Annotating question-answer pairs with their corresponding type(s). | Question Understanding | Pop Culture, Natural Science, History, Law | English | English |
task047_miscellaneous_answering_science_questions |
Answering simple science questions. | Question Answering | Natural Science | English | English |
task048_multirc_question_generation |
Constructing questions based on the information present in the passage. | Question Generation | News, Wikipedia, Law, Justice, History, History -> 9/11 Reports, Anthropology, School Science Textbooks, Fiction | English | English |
task049_multirc_questions_needed_to_answer |
Identifying sentences needed to answer a given question. | Question Answering | News, Wikipedia, Law, Justice, History, History -> 9/11 Reports, Anthropology, School Science Textbooks, Fiction | English | English |
task050_multirc_answerability |
Finding answerability of questions based on a given sentence. | Answerability Classification | News, Wikipedia, Law, Justice, History, History -> 9/11 Reports, Anthropology, School Science Textbooks, Fiction | English | English |
task051_multirc_correct_answer_single_sentence |
Generating correct answer to single-sentence questions. | Question Answering | News, Wikipedia, Law, Justice, History, History -> 9/11 Reports, Anthropology, School Science Textbooks, Fiction | English | English |
task052_multirc_identify_bad_question |
Identifying bad questions. | Text Quality Evaluation | News, Wikipedia, Law, Justice, History, History -> 9/11 Reports, Anthropology, School Science Textbooks, Fiction | English | English |
task053_multirc_correct_bad_question |
Correcting bad questions. | Text Quality Evaluation | News, Wikipedia, Law, Justice, History, History -> 9/11 Reports, Anthropology, School Science Textbooks, Fiction | English | English |
task054_multirc_write_correct_answer |
Writing a Correct Answer for a Reading Comprehension Task. | Question Answering | News, Wikipedia, Law, Justice, History, History -> 9/11 Reports, Anthropology, School Science Textbooks, Fiction | English | English |
task055_multirc_write_incorrect_answer |
Writing Incorrect Answers for a Reading Comprehension Task. | Wrong Candidate Generation | News, Wikipedia, Law, Justice, History, History -> 9/11 Reports, Anthropology, School Science Textbooks, Fiction | English | English |
task056_multirc_classify_correct_answer |
Classifying Good Correct Answers. | Answer Verification | News, Wikipedia, Law, Justice, History, History -> 9/11 Reports, Anthropology, School Science Textbooks, Fiction | English | English |
task057_multirc_classify_incorrect_answer |
Classifying Good Incorrect Answers. | Answer Verification | News, Wikipedia, Law, Justice, History, History -> 9/11 Reports, Anthropology, School Science Textbooks, Fiction | English | English |
task058_multirc_question_answering |
Reading Comprehension Over Multiple Sentences. | Question Answering | News, Wikipedia, Law, Justice, History, History -> 9/11 Reports, Anthropology, School Science Textbooks, Fiction | English | English |
task059_ropes_story_generation |
Generating a story about relations in the given paragraph. | Story Composition | Wikipedia, Natural Science, School Science Textbooks | English | English |
task060_ropes_question_generation |
Constructing questions regarding relations in the given paragraph. | Question Generation | Wikipedia, Natural Science, School Science Textbooks | English | English |
task061_ropes_answer_generation |
Answering questions regarding relations in the given paragraph. | Question Answering | Wikipedia, Natural Science, School Science Textbooks | English | English |
task062_bigbench_repeat_copy_logic |
Generating text that follows simple logical operations such as "repeat", "before", "after" etc. | Program Execution | Formal logic | English | English |
task063_first_i_elements |
Given a list return the first i elements of the list | Program Execution | Mathematics | English | English |
task064_all_elements_except_first_i |
Given a list return all the elements of the list except the first i elements | Program Execution | Mathematics | English | English |
task065_timetravel_consistent_sentence_classification |
Choosing the option that makes a given short story consistent. | Coherence Classification | Commonsense -> Stories | English | English |
task066_timetravel_binary_consistency_classification |
Identifying if the given sentence is consistent with the given story. | Coherence Classification | Commonsense -> Stories | English | English |
task067_abductivenli_answer_generation |
Generating text that completes a story based on the beginning and ending. | Story Composition | Commonsense -> Stories | English | English |
task068_abductivenli_incorrect_answer_generation |
Generating text that modifies a story to be incorrect based on the beginning, middle, and ending. | Story Composition | Commonsense -> Stories | English | English |
task069_abductivenli_classification |
Choosing text that completes a story based on given beginning and ending. | Coherence Classification | Commonsense -> Stories | English | English |
task070_abductivenli_incorrect_classification |
Choosing text that incorrectly completes a story based on given beginning and ending. | Coherence Classification | Commonsense -> Stories | English | English |
task071_abductivenli_answer_generation |
Generating text that completes a story based on given beginning and middle. | Story Composition | Commonsense -> Stories | English | English |
task072_abductivenli_answer_generation |
Generating text that completes a story based on given middle and ending. | Story Composition | Commonsense -> Stories | English | English |
task073_commonsenseqa_answer_generation |
Answer questions based on commonsense knowledge. | Question Answering | Commonsense -> Concepts and Relations | English | English |
task074_squad1.1_question_generation |
Generate guestions based on SQuAD 1.1. | Question Generation | Wikipedia | English | English |
task075_squad1.1_answer_generation |
Generate answers to SQuAD 1.1 questions. | Question Answering | Wikipedia | English | English |
task076_splash_correcting_sql_mistake |
Correct the mistake in a given SQL statement based on feedback. | Text to Code | SQL | English | English |
task077_splash_explanation_to_sql |
Generate a SQL statement based on a description of what the SQL statement does. | Text to Code | SQL | English | English |
task078_all_elements_except_last_i |
Given a list return all the elements of the list except the last i elements | Program Execution | Mathematics | English | English |
task079_conala_concat_strings |
Given a list of strings, concatenate them to form one string. | Program Execution | Code -> Repo -> Stack Overflow | English | English |
task080_piqa_answer_generation |
Generate a solution to a goal regarding physical knowledge about the world. | Question Answering | Commonsense -> Concepts and Relations -> Physical Commonsense | English | English |
task081_piqa_wrong_answer_generation |
Generate an incorrect solution to a goal regarding physical knowledge about the world. | Wrong Candidate Generation | Commonsense -> Concepts and Relations -> Physical Commonsense | English | English |
task082_babi_t1_single_supporting_fact_question_generation |
Generate a question, given a collection of facts. | Question Generation | Commonsense -> Concepts and Relations -> Spatial Commonsense | English | English |
task083_babi_t1_single_supporting_fact_answer_generation |
Generate an answer, given a collection of evidence sentences. | Question Answering | Commonsense -> Concepts and Relations -> Spatial Commonsense | English | English |
task084_babi_t1_single_supporting_fact_identify_relevant_fact |
Given a question and an answer, identify the relevant piece of evidence. | Question Answering | Commonsense -> Concepts and Relations -> Spatial Commonsense | English | English |
task085_unnatural_addsub_arithmetic |
Performing arithmetic with swapped operator symbols. | Mathematics | Mathematics | English | English |
task086_translated_symbol_arithmetic |
Performing arithmetic with translated operator symbols. | Mathematics | Mathematics | Italian | English |
task087_new_operator_addsub_arithmetic |
Performing arithmetic with newly defined operator symbols. | Mathematics | Mathematics | English | English |
task088_identify_typo_verification |
Identify the typo in a sentence. | Spelling Error Detection | Commonsense -> Concepts and Relations | English | English |
task089_swap_words_verification |
Identify the swapped words in a sentence. | Grammar Error Detection | Image Caption | English | English |
task090_equation_learner_algebra |
Answer the given equation. | Mathematics | Mathematics | English | English |
task091_all_elements_from_index_i_to_j |
Given a list return all the elements starting from ith element and ending at jth element | Program Execution | Code | English | English |
task092_check_prime_classification |
Identify whether the number is prime or not. | Mathematics | Mathematics | English | English |
task093_conala_normalize_lists |
Given a list of numbers, normalize the list such that the result adds to 1. | Program Execution | Code -> Repo -> Stack Overflow | English | English |
task094_conala_calculate_mean |
Given a list of numbers, calculate the mean of the list. | Program Execution | Code -> Repo -> Stack Overflow | English | English |
task095_conala_max_absolute_value |
Given a list of numbers, calculate the element with the largest absolute value. | Program Execution | Code -> Repo -> Stack Overflow | English | English |
task096_conala_list_index_subtraction |
Given a list of numbers, subtract each element by its index in the list. | Program Execution | Code -> Repo -> Stack Overflow | English | English |
task097_conala_remove_duplicates |
Given a list of numbers, remove all of the duplicates in the list. | Program Execution | Code -> Repo -> Stack Overflow | English | English |
task098_conala_list_intersection |
Given a two lists of numbers, find the intersection of the two lists. | Program Execution | Code -> Repo -> Stack Overflow | English | English |
task099_reverse_elements_between_index_i_and_j |
Given a list return all the elements starting from ith element and ending at jth element in reverse order | Program Execution | Code | English | English |
task100_concatenate_all_elements_from_index_i_to_j |
Given a list concatenate all the elements starting from ith element and ending at jth element | Program Execution | Code | English | English |
task101_reverse_and_concatenate_all_elements_from_index_i_to_j |
Given a list reverse and then concatenate all the elements starting from ith element and ending at jth element | Program Execution | Code | English | English |
task102_commongen_sentence_generation |
Given a collection of concepts, use them in a coherent sentence. | Data to Text | Captions -> Image Captions | English | English |
task103_facts2story_long_text_generation |
Given 5 facts, write a story that incorporates them. | Story Composition | Story | English | English |
task104_semeval_2019_task10_closed_vocabulary_mathematical_answer_generation |
Answering multiple choices mathematical problem described with a closed-vocabulary. | Question Answering | Mathematics | English | English |
task105_story_cloze-rocstories_sentence_generation |
Given four sentences, predict the next coherent sentence. | Text Completion | Story, Commonsense | English | English |
task106_scruples_ethical_judgment |
Given two actions choose the one that is considered less ethical. | Ethics Classification | Story | English | English |
task107_splash_question_to_sql |
Generate an SQL statement from a question asking for certain data. | Text to Code | Code -> Language -> SQL | English | English |
task108_contextualabusedetection_classification |
Given a text detect whether it's abusive or not. | Toxic Language Detection | Social Media -> Twitter | English | English |
task109_smsspamcollection_spamsmsdetection |
Classify SMS into spam or ham. | Spam Classification | Social Media -> Text Message | English | English |
task110_logic2text_sentence_generation |
Generate a natural language interpretation of the given logical operators. | Code to Text | Code -> Language -> SQL | English | English |
task111_asset_sentence_simplification |
Given a sentence, simplify it so it can be understood by non-native English speakers. | Text Simplification | Wikipedia | English | English |
task112_asset_simple_sentence_identification |
Given two excerpts of text, choose the one that is simpler and easier to understand by non-native speakers. | Text Simplification | Wikipedia | English | English |
task113_count_frequency_of_letter |
Count the frequency of a letter in the given string. | Program Execution | Captions -> Image Captions | English | English |
task114_is_the_given_word_longest |
Identify whether the word is the longest in the sentence. | Linguistic Probing | Captions -> Image Captions | English | English |
task115_help_advice_classification |
Given a text, detect whether it's an advise or not. | Text Categorization | Social Media -> Reddit | English | English |
task116_com2sense_commonsense_reasoning |
Decide whether a sentence is plausible and matches commonsense. | Commonsense Classification | Commonsense -> Concepts and Relations | English | English |
task117_spl_translation_en_de |
Translate English questions to German while preserving named entities in the original language. | Translation | Public Places | English | German |
task118_semeval_2019_task10_open_vocabulary_mathematical_answer_generation |
Answering multiple choices mathematical problem described with an open vocabulary. | Question Answering | Mathematics | English | English |
task119_semeval_2019_task10_geometric_mathematical_answer_generation |
Answering multiple choices geometric problems. | Question Answering | Mathematics | English | English |
task120_zest_text_modification |
Given a question, change the answer with minimum changes. | Question Generation | Government and Politics | English | English |
task121_zest_text_modification |
Given some questions, combine them to have one new question. | Question Rewriting | Government and Politics | English | English |
task122_conala_list_index_addition |
Add lists together based on their index. | Program Execution | Code -> Repo -> Stack Overflow | English | English |
task123_conala_sort_dictionary |
Sort a list of dictionaries based on a given key. | Program Execution | Code -> Repo -> Stack Overflow | English | English |
task124_conala_pair_averages |
Calculate the averages for each two consecutive elements. | Program Execution | Code -> Repo -> Stack Overflow | English | English |
task125_conala_pair_differences |
Calculate the absolute difference for each two consecutive elements. | Program Execution | Code -> Repo -> Stack Overflow | English | English |
task126_scan_structured_text_generation_command_action_all |
Given a natural language command, provide its sequence of actions. | Text to Code | Computer Science -> Machine Learning | English | English |
task127_scan_long_text_generation_action_command_all |
Given a sequence of actions, provide its natural language command. | Code to Text | Computer Science -> Machine Learning | English | English |
task128_scan_structured_text_generation_command_action_short |
Given a short natural language command, provide its sequence of actions. | Text to Code | Computer Science -> Machine Learning | English | English |
task129_scan_long_text_generation_action_command_short |
Given a short sequence of actions, provide its natural language command. | Code to Text | Computer Science -> Machine Learning | English | English |
task130_scan_structured_text_generation_command_action_long |
Given a long natural language command, provide its sequence of actions. | Text to Code | Computer Science -> Machine Learning | English | English |
task131_scan_long_text_generation_action_command_long |
Given a long sequence of actions, provide its natural language command. | Code to Text | Computer Science -> Machine Learning | English | English |
task132_dais_text_modification |
Given a sentence, generate a sentence with same meaning and different grammatical structure. | Paraphrasing | Commonsense | English | English |
task133_winowhy_reason_plausibility_detection |
Detect if a reason that explains an answer to a pronoun coreference resolution question is correct or not. | Coreference Resolution | Commonsense -> Concepts and Relations | English | English |
task134_winowhy_reason_generation |
Give a reason that explains the answer to a pronoun coreference resolution question. | Explanation | Commonsense -> Concepts and Relations | English | English |
task135_winowhy_wrong_reason_generation |
Give a reason that can not explain the answer to a pronoun coreference resolution question. | Wrong Candidate Generation | Commonsense -> Concepts and Relations | English | English |
task136_winowhy_knowledge_categorization |
Categorize the knowledge required to answer a pronoun coreference resolution question. | Commonsense Classification | Commonsense -> Concepts and Relations | English | English |
task137_detoxifying-lms_classification_toxicity |
Given a prompt and two completions, determine which completion is less toxic. | Toxic Language Detection | Social Media -> Twitter | English | English |
task138_detoxifying-lms_classification_fluency |
Given a prompt and two completions, determine which completion is more fluent. | Text Completion | Social Media -> Twitter | English | English |
task139_detoxifying-lms_classification_topicality |
Given a prompt and two completions, determine which completion is more topical. | Text Completion | Social Media -> Twitter | English | English |
task140_detoxifying-lms_classification_style |
Given a prompt and two completions, determine which completion is stylistically more similar. | Text Completion | Social Media -> Twitter | English | English |
task141_odd-man-out_classification_category |
Given a category and set of words, select the word that least belongs. | Word Semantics | Game -> Card Game | English | English |
task142_odd-man-out_classification_no_category |
Given a set of words, select the word that least belongs. | Word Semantics | Game -> Card Game | English | English |
task143_odd-man-out_classification_generate_category |
Given a set of words, select the category that represents the words. | Text Categorization | Game -> Card Game | English | English |
task144_subjqa_question_answering |
Given a review and a question, answer the question with the span of the review. | Question Answering | Reviews -> Movies, Reviews -> TripAdvisor, Reviews -> Restaurants, Reviews -> Movies, Reviews -> Books, Reviews -> Electronics and Grocery | English | English |
task145_afs_argument_similarity_death_penalty |
Given two arguments, determine if they are similar or not. | Text Matching | Government and Politics | English | English |
task146_afs_argument_similarity_gun_control |
Given two arguments, determine if they are similar or not. | Text Matching | Government and Politics | English | English |
task147_afs_argument_similarity_gay_marriage |
Given two arguments, determine if they are similar or not. | Text Matching | Government and Politics | English | English |
task148_afs_argument_quality_gay_marriage |
Given an argument, determine if it's valid. | Text Matching | Government and Politics | English | English |
task149_afs_argument_quality_death_penalty |
Given an argument, determine if it's valid. | Text Matching | Government and Politics | English | English |
task150_afs_argument_quality_gun_control |
Given an argument, determine if it's valid. | Text Matching | Government and Politics | English | English |
task151_tomqa_find_location_easy_clean |
Given an easy story, answer the question regarding the location of an object. | Question Answering | Commonsense -> Stories | English | English |
task152_tomqa_find_location_easy_noise |
Given an easy story with distractor sentences, answer the question regarding the location of an object. | Question Answering | Commonsense -> Stories | English | English |
task153_tomqa_find_location_hard_clean |
Given a hard story, answer the question regarding the location of an object. | Question Answering | Commonsense -> Stories | English | English |
task154_tomqa_find_location_hard_noise |
Given a hard story with distractor sentences, answer the question regarding the location of an object. | Question Answering | Commonsense -> Stories | English | English |
task155_count_nouns_verbs |
Count the number of nouns/verbs in the given sentence. | Pos Tagging | Captions -> Image Captions | English | English |
task156_codah_classification_adversarial |
Given a prompt, select the completion that is the most plausible. | Text Completion | Commonsense -> Concepts and Relations | English | English |
task157_count_vowels_and_consonants |
Count the number of vowels/consonants in the given sentence. | Program Execution | Captions -> Image Captions | English | English |
task158_count_frequency_of_words |
Count the number of occurrences of a word in the given sentence. | Program Execution | Captions -> Image Captions | English | English |
task159_check_frequency_of_words_in_sentence_pair |
Check the frequency of a word in the two sentences. | Program Execution | Captions -> Image Captions | English | English |
task160_replace_letter_in_a_sentence |
Replace a letter in the sentence with another given letter. | Program Execution | Captions -> Image Captions | English | English |
task161_count_words_containing_letter |
Count the number of words in the sentence that contain the given letter. | Program Execution | Captions -> Image Captions | English | English |
task162_count_words_starting_with_letter |
Count the number of words in the sentence that start with the given letter. | Program Execution | Captions -> Image Captions | English | English |
task163_count_words_ending_with_letter |
Count the number of words in the sentence that end with the given letter. | Program Execution | Captions -> Image Captions | English | English |
task164_mcscript_question_answering_text |
Given a passage and question, select the best answer from the given choices. | Question Answering | Narrative -> Everyday Events | English | English |
task165_mcscript_question_answering_commonsense |
Given a passage and question, generate the best answer. | Question Answering | Narrative -> Everyday Events | English | English |
task166_clariq_sentence_generation |
Provide clarification on the given query which is written in natural language. | Question Generation | Dialogue | English | English |
task167_strategyqa_question_generation |
Given a term, write questions based on two or more facts. | Question Generation | Wikipedia | English | English |
task168_strategyqa_question_decomposition |
Given a yes/no question, its answer, and additional information, decompose the question. | Question Decomposition | Wikipedia | English | English |
task169_strategyqa_sentence_generation |
Given a question, write the facts one needs to know in order to answer the question. | Misc. | Wikipedia | English | English |
task170_hotpotqa_answer_generation |
Given a set of context and supporting facts, answer the question asked. | Question Answering | Wikipedia | English | English |
task171_spl_translation_en_es |
Translate English questions to Spanish while preserving named entities in the original language. | Translation | Public Places | English | Spanish |
task172_spl_translation_en_fa |
Translate English questions to Farsi while preserving named entities in the original language. | Translation | Public Places | English | Persian |
task173_spl_translation_en_it |
Translate English questions to Italian while preserving named entities in the original language. | Translation | Public Places | English | Italian |
task174_spl_translation_en_ja |
Translate English questions to Japanese while preserving named entities in the original language. | Translation | Public Places | English | Japanese |
task175_spl_translation_en_pl |
Translate English questions to Polish while preserving named entities in the original language. | Translation | Public Places | English | Polish |
task176_break_decompose_questions |
Break a question into the steps needed to answer the question. | Question Decomposition | Miscellaneous | English | English |
task177_para-nmt_paraphrasing |
Given a sentence, rephrase it using another words while retaining meaning same as input. | Paraphrasing | Miscellaneous | English | English |
task178_quartz_question_answering |
Given a question, select the correct answer from the given options using an explanation. | Question Answering | Natural Science | English | English |
task179_participant_extraction |
Given a sentence from a medical study paper, select the tokens representing information about participants. | Information Extraction | Medicine | English | English |
task180_intervention_extraction |
Given a sentence from a medical study paper, select the tokens representing information about intervention in the study. | Information Extraction | Medicine | English | English |
task181_outcome_extraction |
Given a sentence from a medical study paper, select the tokens representing information about outcome of the study. | Information Extraction | Medicine | English | English |
task182_duorc_question_generation |
Writing a question based on a given plot. | Question Generation | Movies | English | English |
task183_rhyme_generation |
Given an input word, generate a list of words that rhyme exactly with the input. | Misc. | Miscellaneous | English | English |
task184_break_generate_question |
Generate a question based on the given steps used to answer it. | Question Generation | Wikipedia | English | English |
task184_snli_entailment_to_neutral_text_modification |
Given two sentences that agree with each other, modify the second sentence so that they do not clearly agree or disagree. | Sentence Composition | Captions -> Image Captions | English | English |
task185_snli_contradiction_to_neutral_text_modification |
Given two sentences that don't agree with each other, modify the second sentence so that they do not clearly agree or disagree. | Sentence Composition | Captions -> Image Captions | English | English |
task186_snli_contradiction_to_entailment_text_modification |
Given two sentences that don't agree with each other, modify the second sentence so that they clearly agree with each other. | Sentence Composition | Captions -> Image Captions | English | English |
task187_snli_entailment_to_contradiction_text_modification |
Given two sentences that agree with each other, modify the second sentence so that they clearly do not agree. | Sentence Composition | Captions -> Image Captions | English | English |
task188_snli_neutral_to_entailment_text_modification |
Given two sentences that do not clearly agree or disagree with each other, modify the second sentence so that they clearly agree. | Sentence Composition | Captions -> Image Captions | English | English |
task189_snli_neutral_to_contradiction_text_modification |
Given two sentences that do not clearly agree or disagree with each other, modify the second sentence so that they clearly do not agree. | Sentence Composition | Captions -> Image Captions | English | English |
task190_snli_classification |
Given two sentences choose whether they agree/disagree/neither with each other. | Textual Entailment | Captions -> Image Captions | English | English |
task191_hotpotqa_question_generation |
Given a set of context, supporting facts and an answer, generate the question asked based on them. | Question Generation | Wikipedia | English | English |
task192_hotpotqa_sentence_generation |
Given a context paragraph, question and corresponding answer, generate the supporting facts that helps in answering question. | Explanation | Wikipedia | English | English |
task193_duorc_question_generation |
Generate a question based on a given plot. | Question Generation | Movies | English | English |
task194_duorc_answer_generation |
Given a plot and a question, answer the question based on the plot. | Question Answering | Movies | English | English |
task195_sentiment140_classification |
Given a tweet, classify its sentiment as either positive or negative. | Sentiment Analysis | Social Media -> Twitter | English | English |
task196_sentiment140_answer_generation |
Given a tweet and boolean question, generate yes or no. | Sentiment Analysis | Social Media -> Twitter | English | English |
task197_mnli_domain_answer_generation |
Given two sentences, write a single word describing the common genre to which they belong. | Text Categorization | History, Fiction, Dialogue, Law, Government and Politics | English | English |
task198_mnli_domain_classification |
Given two sentences and 10 genre choices, determine the genre to which the sentences belong. | Text Categorization | History, Fiction, Dialogue, Law, Government and Politics | English | English |
task199_mnli_classification |
Given 2 sentences, determine if they clearly agree or disagree with each other or if they cannot be answered. | Textual Entailment | History, Fiction, Dialogue, Law, Government and Politics | English | English |
task200_mnli_entailment_classification |
Given a context statement and three sentences as choices, select the sentence that agrees with the context statement. | Textual Entailment | History, Fiction, Dialogue, Law, Government and Politics | English | English |
task201_mnli_neutral_classification |
Given a context statement and three sentences as choices, select the sentence that neither clearly agrees nor disagrees with the context statement. | Textual Entailment | History, Fiction, Dialogue, Law, Government and Politics | English | English |
task202_mnli_contradiction_classification |
Given a context statement and 3 sentences as choices, choose the sentence that clearly disagrees with the context statement. | Textual Entailment | History, Fiction, Dialogue, Law, Government and Politics | English | English |
task203_mnli_sentence_generation |
Given a context statement, genre, and label indicating agree/disagree/neither with respect to the context statement, generate a sentence that follows the genre and label specifications. | Sentence Composition | History, Fiction, Dialogue, Law, Government and Politics | English | English |
task204_mnli_same_genre_classification |
Given two sentences and the genre they should belong to, determine if they belong to the same genre or not. | Text Categorization | History, Fiction, Dialogue, Law, Government and Politics | English | English |
task205_remove_even_elements |
Given a list of integers, remove all elements that are even. | Program Execution | Mathematics | English | English |
task206_collatz_conjecture |
Given a list of integers, compute the next number in the 3n+1 problem. | Program Execution | Mathematics | English | English |
task207_max_element_lists |
Given a list of lists of integers compute the max value for each list. | Program Execution | Mathematics | English | English |
task208_combinations_of_list |
Given a list of integers of length n, find all possible combinations without replacement of length n-1. | Program Execution | Mathematics | English | English |
task209_stancedetection_classification |
Given a topic and an argument, detect whether topic is in favor or against in the argument. | Stance Detection | Debatepedia | English | English |
task210_logic2text_structured_text_generation |
Given a natural language interpretation, generate a command using logical operations. | Text to Code | Wikipedia, Logic -> Propositional Logic | English | English |
task211_logic2text_classification |
Given a command and corresponding interpretation, classify whether it is the right interpretation or not. | Text to Code | Wikipedia, Logic -> Propositional Logic | English | English |
task212_logic2text_classification |
Given a command, classify the command in one of seven logic types. | Text to Code | Wikipedia, Logic -> Propositional Logic | English | English |
task213_rocstories_correct_ending_classification |
Given the title and the first four sentences of a five sentence story, choose the correct story ending. | Text Completion | Narrative, Story | English | English |
task214_rocstories_incorrect_ending_classification |
Given the title and the first four sentences of a five sentence story, choose the incorrect story ending. | Text Completion | Narrative, Story | English | English |
task215_rocstories_incorrect_answer_generation |
Given the title and the first four sentences of a five sentence story, write an incorrect story ending. | Text Completion | Narrative, Story | English | English |
task216_rocstories_correct_answer_generation |
Given the title and the first four sentences of a five sentence story, write a correct story ending. | Text Completion | Narrative, Story | English | English |
task217_rocstories_ordering_answer_generation |
Given a five sentence story in shuffled order and the title, put the story in the correct order. | Sentence Ordering | Narrative, Story | English | English |
task218_rocstories_swap_order_answer_generation |
Given a five sentence story and the title, determine which two sentences must be swapped so that the story makes complete sense. | Sentence Ordering | Narrative, Story | English | English |
task219_rocstories_title_answer_generation |
Given a five sentence story, generate an appropriate title for the story. | Title Generation | Narrative, Story | English | English |
task220_rocstories_title_classification |
Given a five sentence story, choose an appropriate title for the story from the given options. | Title Generation | Narrative, Story | English | English |
task221_rocstories_two_choice_classification |
Given three sentences and title of a five sentence story, choose which two sentences from the options given will complete the story. | Text Completion | Narrative, Story | English | English |
task222_rocstories_two_chioce_slotting_classification |
Given three sentences and title of a five sentence story, choose which two sentences from the given options will complete the story. | Text Completion | Narrative, Story | English | English |
task223_quartz_explanation_generation |
Given a question and its answer, generate an explanation statement. | Explanation | Natural Science | English | English |
task224_scruples_anecdotes_ethical_judgment |
Given an anecdote, judge whether the author is ethically correct or not. | Ethics Classification | Story | English | English |
task225_english_language_answer_generation |
Given a basic English language related question generate the answer with proper context, definitions, and examples. | Question Answering | Code -> Repo -> Stack Overflow, Linguistics | English | English |
task226_english_language_answer_relevance_classification |
Given a question and answer pair, detect whether the answer is acceptable or not. | Answerability Classification | Code -> Repo -> Stack Overflow, Linguistics | English | English |
task227_clariq_classification |
Given a query and its clarification, classify whether clarification is proper or not by providing 'Yes' or 'No'. | Question Understanding | Dialogue | English | English |
task228_arc_answer_generation_easy |
Given a easy science question, provide the answer based on scientific facts and reasoning. | Question Answering | School Science Textbooks | English | English |
task229_arc_answer_generation_hard |
Given a hard science question, provide the answer based on scientific facts and reasoning. | Question Answering | School Science Textbooks | English | English |
task230_iirc_passage_classification |
Given 3 passages and a question, determine which passage can be used to answer the question. | Question Answering | Wikipedia | English | English |
task231_iirc_link_classification |
Given a question, context passage, and terms from the passage for further information search, determine which term can be used to answer the question. | Question Answering | Wikipedia | English | English |
task232_iirc_link_number_classification |
Given a question and context passage, determine if further information on more than one term from the passage is needed to answer the question. | Answerability Classification | Wikipedia | English | English |
task233_iirc_link_exists_classification |
Given a question and context passage, determine if the passage has any terms that can be used to obtain further information needed to answer the question. | Answerability Classification | Wikipedia | English | English |
task234_iirc_passage_line_answer_generation |
Given a question and context passage, determine which sentence in the passage has terms that can be used to obtain further information needed to answer the question. | Question Answering | Wikipedia | English | English |
task235_iirc_question_from_subtext_answer_generation |
Given a context statement, further information on a linked term in the statement, and an answer term, generate a question that can use the information provided to obtain the given answer | Question Generation | Wikipedia | English | English |
task236_iirc_question_from_passage_answer_generation |
Given a context passage, further information on a linked term in the statement, and an answer term, generate a question that can use the information provided to obtain the given answer | Question Generation | Wikipedia | English | English |
task237_iirc_answer_from_subtext_answer_generation |
Given a context statement, further information on a linked term in the statement, and a question, generate an answer that can use the information provided to solve the question | Question Answering | Wikipedia | English | English |
task238_iirc_answer_from_passage_answer_generation |
Given a context passage, further information on a linked term in the statement, and a question, generate an answer that can use the information provided to solve the question | Question Answering | Wikipedia | English | English |
task239_tweetqa_answer_generation |
Given a context paragraph of the tweet and question, generate a correct answer. | Question Answering | Social Media -> Twitter | English | English |
task240_tweetqa_question_generation |
Given a context paragraph of the tweet and answer, generate a correct question. | Question Generation | Social Media -> Twitter | English | English |
task241_tweetqa_classification |
Given a context paragraph of the tweet, question and corresponding answer, generate a label whether the answer is right or wrong. | Answer Verification | Social Media -> Twitter | English | English |
task242_tweetqa_classification |
Given a context paragraph of the tweet, question and corresponding answer, generate a label whether the context is helpful in answering question or not. | Answerability Classification | Social Media -> Twitter | English | English |
task243_count_elements_in_set_intersection |
Count the number of elements in the intersection of two given sets. | Program Execution | Mathematics | English | English |
task244_count_elements_in_set_union |
Count the number of elements in the union of two given sets. | Program Execution | Mathematics | English | English |
task245_check_presence_in_set_intersection |
Check the presence of an element in the intersection of two given sets. | Program Execution | Mathematics | English | English |
task246_dream_question_generation |
Given a conversation, generate a multiple-choice question based on it. | Question Generation | Dialogue, Natural Science -> School Science Textbooks | English | English |
task247_dream_answer_generation |
Given a conversation and a question, answer the question based on the conversation. | Question Answering | Dialogue, Natural Science -> School Science Textbooks | English | English |
task248_dream_classification |
Given a conversation and a question, classify the question. | Question Understanding | Dialogue, Natural Science -> School Science Textbooks | English | English |
task249_enhanced_wsc_pronoun_disambiguation |
Given a sentence and a pronoun, decide which one of the choices the pronoun is referring to. | Coreference Resolution | Dialogue, Narrative | English | English |
task250_spl_translation_en_ar |
Translate English questions to Arabic while preserving named entities in the original language. | Translation | Public Places -> Restaurants | English | Arabic |
task251_spl_translation_en_fi |
Translate English questions to Finnish while preserving named entities in the original language. | Translation | Public Places -> Restaurants | English | Finnish |
task252_spl_translation_en_tr |
Translate English questions to Turkish while preserving named entities in the original language. | Translation | Public Places -> Restaurants | English | Turkish |
task253_spl_translation_en_zh |
Translate English questions to Chinese while preserving named entities in the original language. | Translation | Public Places -> Restaurants | English | Chinese |
task254_spl_translation_fi_en |
Translate Finnish questions to English while preserving named entities in the original language. | Translation | Public Places -> Restaurants | Finnish | English |
task255_spl_translation_it_en |
Translate Italian questions to English while preserving named entities in the original language. | Translation | Public Places -> Restaurants | Italian | English |
task256_spl_translation_de_en |
Translate German questions to English while preserving named entities in the original language. | Translation | Public Places -> Restaurants | German | English |
task257_spl_translation_ar_en |
Translate Arabic questions to English while preserving named entities in the original language. | Translation | Public Places -> Restaurants | Arabic | English |
task258_spl_translation_fa_en |
Translate Farsi questions to English while preserving named entities in the original language. | Translation | Public Places -> Restaurants | Persian | English |
task259_spl_translation_tr_en |
Translate Turkish questions to English while preserving named entities in the original language. | Translation | Public Places -> Restaurants | Turkish | English |
task260_spl_translation_zh_en |
Translate Chinese questions to English while preserving named entities in the original language. | Translation | Public Places -> Restaurants | Chinese | English |
task261_spl_translation_es_en |
Translate Spanish questions to English while preserving named entities in the original language. | Translation | Public Places -> Restaurants | Spanish | English |
task262_spl_translation_ja_en |
Translate Japanese questions to English while preserving named entities in the original language. | Translation | Public Places -> Restaurants | Japanese | English |
task263_spl_translation_pl_en |
Translate Polish questions to English while preserving named entities in the original language. | Translation | Public Places -> Restaurants | Polish | English |
task264_paper_reviews_accept_or_reject_classification |
Given a set of reviews, classify paper into accept or reject | Paper Review | Conference | Spanish, English | English |
task265_paper_reviews_language_identification |
Given a paper review, identify it is in the english or spanish language | Language Identification | Conference | Spanish, English | English |
task266_paper_reviews_reviewer_perspective_classification |
Given a paper review, classify into five evaluation metric | Sentiment Analysis | Conference | Spanish, English | English |
task267_concatenate_and_reverse_all_elements_from_index_i_to_j |
Given a list concatenate and then mirror/reverse all the elements starting from ith element and ending at jth element | Program Execution | Mathematics | English | English |
task268_casehold_legal_answer_generation |
Given a prompt from a judicial decision and multiple potential holdings, choose the correct option. | Text Completion | Law | English | English |
task269_csrg_counterfactual_story_generation |
Given premise, initial context with ending, and counterfactul context, generate new story ending supporting counterfactual. | Story Composition | Story | English | English |
task270_csrg_counterfactual_context_generation |
Given premise, initial context with ending, and new counterfactul ending, generate counterfactual context which supports the new story ending. | Story Composition | Story | English | English |
task271_europarl_translation |
Translate a sentence in Bulgarian to English. | Translation | Government and Politics | Bulgarian | English |
task272_europarl_translation |
Translate a sentence in English to Bulgarian. | Translation | Government and Politics | English | Bulgarian |
task273_europarl_classification |
Given a sentence in Bulgarian and its corresponding English translation, verify that the translation is correct. | Text Matching | Government and Politics | Bulgarian, English | English |
task274_overruling_legal_classification |
Given a sentence, classify it into overruling or non-overruling. | Text Categorization | Law | English | English |
task275_enhanced_wsc_paraphrase_generation |
Given a sentence and an aspect, paraphrase the sentence changing that aspect. | Sentence Perturbation | Dialogue, Narrative | English | English |
task276_enhanced_wsc_classification |
Given a sentence and its paraphrase, decide what is the difference between them. | Text Matching | Dialogue, Narrative | English | English |
task277_stereoset_sentence_generation_stereotype |
Generate sentences with stereotype given context. | Fill in The Blank | Stereotypes | English | English |
task278_stereoset_sentence_generation_antistereotype |
Generate sentences with anti-stereotype given context. | Fill in The Blank | Stereotypes | English | English |
task279_stereoset_classification_stereotype |
Classify sentences into stereotype, anti-stereotype, and unrelated. | Stereotype Detection | Stereotypes | English | English |
task280_stereoset_classification_stereotype_type |
Classify sentences into four kinds of stereotypes, including gender, profession, race, and religion. | Text Categorization | Stereotypes | English | English |
task281_points_of_correspondence |
Find the entity or event that is in common between the given three sentences. | Overlap Extraction | News | English | English |
task282_scruples_event_time |
Given an anecdote, find whether it has already happened or it may happen in the future. | Text Categorization | Narrative, Story | English | English |
task283_dream_incorrect_answer_generation |
Given a conversation and a question, write an incorrect answer to the question. | Wrong Candidate Generation | Dialogue, Natural Science -> School Science Textbooks | English | English |
task284_imdb_classification |
Given a movie review, classify its sentiment into positive or negative. | Sentiment Analysis | Reviews -> Movies | English | English |
task285_imdb_answer_generation |
Given a movie review and boolean question, generate answer yes or no. | Sentiment Analysis | Reviews -> Movies | English | English |
task286_olid_offense_judgment |
Given a tweet judge whether its offensive or not. | Toxic Language Detection | Social Media -> Twitter | English | English |
task287_casehold_legal_incorrect_answer_generation |
Given a prompt from a judicial decision and multiple potential holdings, choose one of the incorrect options. | Wrong Candidate Generation | Law | English | English |
task288_gigaword_summarization |
Given a text of article, generate a title for the article. | Title Generation | News | English | English |
task289_gigaword_summarization |
Given the text of an article and its title, decide whether the title is appropriate for the article. | Text Matching | News | English | English |
task290_tellmewhy_question_answerability |
Given a short story and a question, decide whether or not the question is answerable. | Answerability Classification | Story | English | English |
task291_semeval_2020_task4_commonsense_validation |
Given two statements, choose the one that makes less sense. | Commonsense Classification | Commonsense -> Concepts and Relations | English | English |
task292_storycommonsense_character_text_generation |
Given a short story, provide all the characters in that story. | Information Extraction | Story | English | English |
task293_storycommonsense_emotion_text_generation |
Given a sentence, context (optional) and character; provide emotions expressed by the character in the sentence. | Sentiment Analysis | Story | English | English |
task294_storycommonsense_motiv_text_generation |
Given a sentence, context (optional) and character; provide motivation of the character in the sentence. | Intent Identification | Story | English | English |
task295_semeval_2020_task4_commonsense_reasoning |
Given a statement against commonsense and 3 reasons, choose the best reason explaining why the statement is against commonsense. | Explanation | Commonsense -> Concepts and Relations | English | English |
task296_storycloze_correct_end_classification |
Given four sentences of five sentence story, select correct answer for last (fifth) sentence from the given option. | Text Completion | Story | English | English |
task297_storycloze_incorrect_end_classification |
Given four sentences of five sentence story, select incorrect answer for last (fifth) sentence from the given option. | Text Completion | Story | English | English |
task298_storycloze_correct_end_classification |
Given four sentences of five sentence story and fifth sentence, classify whether fifth sentence is proper or not by providing 'Yes' or 'No'. | Coherence Classification | Story | English | English |
task299_storycloze_sentence_generation |
Given four sentences of five sentence story, provide the position and missing part (fifth sentence) of the story. | Text Completion | Story | English | English |
task300_storycloze_order_generation |
Given five sentences of story (sentences are shuffled), provide correct order of the story. | Sentence Ordering | Story, Commonsense | English | English |
task301_record_question_generation |
Given a passage, generate a fill-in-the-gap question based on it. | Question Generation | News | English | English |
task302_record_classification |
Given a passage and a question, classify the answer to the question based on the options. | Question Answering | News | English | English |
task303_record_incorrect_answer_generation |
Given a passage and a question, write an incorrect answer for the question. | Wrong Candidate Generation | News | English | English |
task304_numeric_fused_head_resolution |
Given a dialogue and a highlighted number, decide what does the number refer to | Coreference Resolution | Dialogue | English | English |
task305_jeopardy_answer_generation_normal |
Given a category and a trivia clue of relatively easy difficulty, generate the best answer. | Misc. | Knowledge Base | English | English |
task306_jeopardy_answer_generation_double |
Given a category and a trivia clue of relatively medium difficulty, generate the best answer. | Misc. | Knowledge Base | English | English |
task307_jeopardy_answer_generation_final |
Given a category and a trivia clue of relatively hard difficulty, generate the best answer. | Misc. | Knowledge Base | English | English |
task308_jeopardy_answer_generation_all |
Given a category and a trivia clue of varying difficulties, generate the best answer. | Misc. | Knowledge Base | English | English |
task309_race_answer_generation |
Given an article, a question and four options; provide correct answer for the question based on the article. | Question Answering | English Exams | English | English |
task310_race_classification |
Given an article, a question and four options; provide incorrect answer for the question based on the article. | Question Answering | English Exams | English | English |
task311_race_question_generation |
Generate a question based on the given article and an answer. | Question Generation | English Exams | English | English |
task312_europarl_sv_en_translation |
Given a Swedish sentence, convert it into English. | Translation | Government and Politics | Swedish | English |
task313_europarl_en_sv_translation |
Given an English sentence, convert it into Swedish. | Translation | Government and Politics | English | Swedish |
task314_europarl_sv-en_classification |
Given a Swedish sentence and its corresponding English sentence, classify whether it is correct or not. | Text Matching | Government and Politics | Swedish, English | English |
task315_europarl_sv-en_language_identification |
Given a sentence, identify whether it is in Swedish or English. | Text Matching | Government and Politics | Swedish, English | English |
task316_crows-pairs_classification_stereotype |
Classify a sentence into stereotype or anti-stereotype | Stereotype Detection | Stereotypes | English | English |
task317_crows-pairs_classification_stereotype_type |
Classify a sentence into different types of stereotype | Stereotype Detection | Stereotypes | English | English |
task318_stereoset_classification_gender |
Given a target pertaining to gender in the two sentences, determine if it is a stereotype. | Stereotype Detection | Stereotypes | English | English |
task319_stereoset_classification_profession |
Given a target pertaining to profession in the two sentences, determine if it is a stereotype. | Stereotype Detection | Stereotypes | English | English |
task320_stereoset_classification_race |
Given a target pertaining to race in the two sentences, determine if it is a stereotype. | Stereotype Detection | Stereotypes | English | English |
task321_stereoset_classification_religion |
Given a target pertaining to religion in the two sentences, determine if it is a stereotype. | Stereotype Detection | Stereotypes | English | English |
task322_jigsaw_classification_threat |
Given a comment from online platforms, classify whether or not it contains threats. | Toxic Language Detection | Social Media | English | English |
task323_jigsaw_classification_sexually_explicit |
Given a comment, classify whether it is sexually explicit or not. | Toxic Language Detection | Social Media | English | English |
task324_jigsaw_classification_disagree |
Given a comment, classify whether it expresses disagreement. | Toxic Language Detection | Social Media | English | English |
task325_jigsaw_classification_identity_attack |
Given a comment, classify whether it attacks a person's identity or not. | Toxic Language Detection | Social Media | English | English |
task326_jigsaw_classification_obscene |
Given a comment, classify whether it conveys obscenity or not. | Toxic Language Detection | Social Media | English | English |
task327_jigsaw_classification_toxic |
Given a comment from online platforms, classify whether it is toxic or not. | Toxic Language Detection | Social Media | English | English |
task328_jigsaw_classification_insult |
Given a comment from online platforms, classify whether it is an insult or not. | Toxic Language Detection | Social Media | English | English |
task329_gap_classification |
Given a text containing an ambiguous pronoun, a pronoun, and two candidate names, determine what the pronoun refers to and classify the answers into A, B, or Neither | Coreference Resolution | Wikipedia | English | English |
task330_gap_answer_generation |
Given a text containing an ambiguous pronoun and a pronoun, write the name that the pronoun refers to | Coreference Resolution | Wikipedia | English | English |
task331_gap_incorrect_answer_generation |
Given a text containing an ambiguous pronoun and a pronoun, write an implausible answer to the question of what is the pronoun reference | Wrong Candidate Generation | Wikipedia | English | English |
task332_tellmewhy_answer_generation |
Given a short story and a question, answer the question based on the events of the story. | Question Answering | Story | English | English |
task333_hateeval_classification_hate_en |
Given a post in English, classify it into hateful or non-hateful | Toxic Language Detection | Social Media -> Twitter | English | English |
task334_hateeval_classification_hate_es |
Given a post in Spanish, classify it into hateful or non-hateful | Toxic Language Detection | Social Media -> Twitter | Spanish | English |
task335_hateeval_classification_aggresive_en |
Given a hateful post in English, classify it into aggresive or non-aggresive | Toxic Language Detection | Social Media -> Twitter | English | English |
task336_hateeval_classification_aggresive_es |
Given a hateful post in Spanish, classify it into aggresive or non-aggresive | Toxic Language Detection | Social Media -> Twitter | Spanish | English |
task337_hateeval_classification_individual_en |
Given a hateful post in English, classify the target being harassed into individual or generic | Toxic Language Detection | Social Media -> Twitter | English | English |
task338_hateeval_classification_individual_es |
Given a hateful post in Spanish, classify the target being harassed into individual or generic | Toxic Language Detection | Social Media -> Twitter | Spanish | English |
task339_record_answer_generation |
Given a passage and a question, answer the question based on the passage. | Question Answering | News | English | English |
task340_winomt_classification_gender_pro |
Given a sentence and a profession that is mentioned in the sentence, identify its gender. pro means the gender aggrees with the cultural stereotype of the profession | Gender Classification | Miscellaneous | English | English |
task341_winomt_classification_gender_anti |
Given a sentence and a profession that is mentioned in the sentence, identify its gender. anti means the gender disagrees with the cultural stereotype of the profession | Gender Classification | Miscellaneous | English | English |
task342_winomt_classification_profession_pro |
Given a sentence and a gender, identify the profession mentioned in the sentence with the given gender. pro means the gender aggrees with the cultural stereotype of the profession | Gender Classification | Miscellaneous | English | English |
task343_winomt_classification_profession_anti |
Given a sentence and a gender, identify the profession mentioned in the sentence with the given gender. anti means the gender disaggrees with the cultural stereotype of the profession | Gender Classification | Miscellaneous | English | English |
task344_hybridqa_answer_generation |
Given a question, answer the question based on your knowledge. | Question Answering | Wikipedia | English | English |
task345_hybridqa_answer_generation |
Given a question, write the part-of-speech tag for each word in the question. | Pos Tagging | Wikipedia | English | English |
task346_hybridqa_classification |
Given a question, a word, and a POS tag, determine whether the POS tag is True or False based on the part-of-speech tag of the given word in the question. | Pos Tagging | Wikipedia | English | English |
task347_hybridqa_incorrect_answer_generation |
Given a question about part-of-speech tag of a word in the question, write an implausible POS tag to the question. | Pos Tagging | Wikipedia | English | English |
task348_squad2.0_unanswerable_question_generation |
Given a passage, generate a question that cannot be answered based on the passage. | Question Generation | Wikipedia | English | English |
task349_squad2.0_answerable_unanswerable_question_classification |
Given a passage and a question, classify whether or not the question is answerable from the passage. | Answerability Classification | Wikipedia | English | English |
task350_winomt_classification_gender_identifiability_pro |
Given a sentence and a profession, identify whether the profession's gender is identifiable. pro means the gender agrees with the cultural stereotype of the profession | Gender Classification | Miscellaneous | English | English |
task351_winomt_classification_gender_identifiability_anti |
Given a sentence and a profession, identify whether the profession's gender is identifiable. anti means the gender disagrees with the cultural stereotype of the profession | Gender Classification | Miscellaneous | English | English |
task352_coda-19_classification |
given a paragraph, classify into these categories: background, purpose, method, finding/contribution, and other. | Section Classification | Biology | English | English |
task353_casino_classification_negotiation_elicit_pref |
Detecting the usage of elicit-pref negotiation strategy in dialogue utterances. | Negotiation Strategy Detection | Dialogue | English | English |
task354_casino_classification_negotiation_no_need |
Detecting the usage of no-need negotiation strategy in dialogue utterances. | Negotiation Strategy Detection | Dialogue | English | English |
task355_casino_classification_negotiation_other_need |
Detecting the usage of other-need negotiation strategy in dialogue utterances. | Negotiation Strategy Detection | Dialogue | English | English |
task356_casino_classification_negotiation_self_need |
Detecting the usage of self-need negotiation strategy in dialogue utterances. | Negotiation Strategy Detection | Dialogue | English | English |
task357_casino_classification_negotiation_small_talk |
Detecting the usage of small-talk negotiation strategy in dialogue utterances. | Negotiation Strategy Detection | Dialogue | English | English |
task358_casino_classification_negotiation_uv_part |
Detecting the usage of uv-part negotiation strategy in dialogue utterances. | Negotiation Strategy Detection | Dialogue | English | English |
task359_casino_classification_negotiation_vouch_fair |
Detecting the usage of vouch-fair negotiation strategy in dialogue utterances. | Negotiation Strategy Detection | Dialogue | English | English |
task360_spolin_yesand_response_generation |
Given a prompt, generate the "yes, ands" response | Dialogue Generation | Dialogue | English | English |
task361_spolin_yesand_prompt_response_classification |
Given a prompt and a response, classify whether the response is "yes, ands" type | Dialogue Generation | Dialogue | English | English |
task362_spolin_yesand_prompt_response_sub_classification |
Given a prompt and two responses, identify which response is "yes, ands" type | Dialogue Act Recognition | Dialogue | English | English |
task363_sst2_polarity_classification |
Given a sentence from a movie review, classify the sentence to positive or negative sentiment. | Sentiment Analysis | Reviews -> Movies | English | English |
task364_regard_social_impact_classification |
Given a sentence about a person, decide what is the impact of that sentence on the society's perception of that person. | Text Categorization | Miscellaneous | English | English |
task365_synthetic_remove_vowels |
Given a string remove any vowels in that string. | Program Execution | Code, Mathematics | English | English |
task366_synthetic_return_primes |
Given a list of integers return a number if it is prime. | Program Execution | Code, Mathematics | English | English |
task367_synthetic_remove_floats |
Given a list of numbers remove any number if it is not an integer | Program Execution | Code, Mathematics | English | English |
task368_synthetic_even_or_odd_calculation |
Given a list of integers divide even numbers by 4 and multiply odd numbers by 4 then add 2 | Program Execution | Code, Mathematics | English | English |
task369_synthetic_remove_odds |
Given a list of integers remove any integer if it is odd | Program Execution | Code, Mathematics | English | English |
task370_synthetic_remove_divisible_by_3 |
Given a list of integers remove any integer if it is divisible by 3 | Program Execution | Code, Mathematics | English | English |
task371_synthetic_product_of_list |
Given a list of lists of integers, find the product of every inner list | Program Execution | Code, Mathematics | English | English |
task372_synthetic_palindrome_numbers |
Given a list of integers return an integer if the first and last digit are the same | Program Execution | Code, Mathematics | English | English |
task373_synthetic_round_tens_place |
Given a list of integers round them to the tens place | Program Execution | Code, Mathematics | English | English |
task374_synthetic_pos_or_neg_calculation |
Given a list of integers multiply the negative integers by -3 multiply the even integers by 2 | Program Execution | Code, Mathematics | English | English |
task375_classify_type_of_sentence_in_debate |
Given a debate topic and a sentence from the debate, classify the type of the sentence. | Text Categorization | Government and Politics | English | English |
task376_reverse_order_of_words |
Reverse the order of words in the given sentence | Program Execution | Captions -> Image Captions | English | English |
task377_remove_words_of_given_length |
Remove all words of a given length in the sentence | Program Execution | Captions -> Image Captions | English | English |
task378_reverse_words_of_given_length |
Reverse all words of a given length in the sentence | Program Execution | Captions -> Image Captions | English | English |
task379_agnews_topic_classification |
Given a news article, classify the article's topic to four classes. | Text Categorization | News | English | English |
task380_boolq_yes_no_question |
Given a passage and a yes/no question, answer the question based on the passage | Question Answering | Wikipedia | English | English |
task381_boolq_question_generation |
Given a passage, generate a yes/no question that can be answered based on the passage | Question Generation | Wikipedia | English | English |
task382_hybridqa_answer_generation |
Given a question about part-of-speech tag of a word in the question, answer the question | Pos Tagging | Wikipedia | English | English |
task383_matres_classification |
Given a context and a verb, answer if the given verb can be anchored in time or not | Misc. | News | English | English |
task384_socialiqa_question_classification |
You're given context, an answer and question. Your task is to classify whether the question is correct or not. | Question Understanding | Commonsense -> Concepts and Relations -> Social Commonsense | English | English |
task385_socialiqa_incorrect_answer_generation |
You're given a context, a question, three options. Your task is to return an incorrect answer from the option. | Question Answering | Commonsense -> Concepts and Relations -> Social Commonsense | English | English |
task386_semeval_2018_task3_irony_detection |
Given a tweet judge whether it contains irony or not. | Irony Detection | Social Media -> Twitter | English | English |
task387_semeval_2018_task3_irony_classification |
Given a tweet Classify the kind of irony it has. | Irony Detection | Social Media -> Twitter | English | English |
task388_torque_token_classification |
Given a passage, identify a token from the passage representing an event | Information Extraction | News | English | English |
task389_torque_generate_temporal_question |
Given a passage, generate a temporal question | Question Generation | News | English | English |
task390_torque_text_span_selection |
Given a passage, a temporal question and a list of events in the passage, return a text span from the list of events that answers the given question | Question Answering | News | English | English |
task391_causal_relationship |
Given two sentences, decide whether the second sentence can be the result of the first one. | Cause Effect Classification | Commonsense | English | English |
task392_inverse_causal_relationship |
Given two sentences, decide whether the first sentence can be the result of the second one. | Cause Effect Classification | Commonsense | English | English |
task393_plausible_result_generation |
Given a sentence, write another sentence that is a likely result of it. | Cause Effect Classification | Commonsense | English | English |
task394_persianqa_question_generation |
Given a passage, generate a question based on it. | Question Generation | Wikipedia | Persian | Persian |
task395_persianqa_answer_generation |
Given a passage and a question, answer the question based on the passage | Question Answering | Wikipedia | Persian | Persian |
task396_persianqa_classification |
Given a passage and a question, check whether the question is answerable based on the passage or not | Answerability Classification | Wikipedia | Persian | English |
task397_semeval_2018_task1_tweet_anger_detection |
Given a tweet judge whether the author was angry or not | Sentiment Analysis | Social Media -> Twitter | English | English |
task398_semeval_2018_task1_tweet_joy_detection |
Given a tweet judge whether the author was happy or not | Sentiment Analysis | Social Media -> Twitter | English | English |
task399_semeval_2018_task1_tweet_sadness_detection |
Given a tweet judge whether the author was sad or not | Sentiment Analysis | Social Media -> Twitter | English | English |
task400_paws_paraphrase_classification |
Given two sentences, judge whether they are paraphrases of each other | Text Matching | Wikipedia | English | English |
task401_numeric_fused_head_reference |
Given a dialogue and a highlighted number, choose the entity the number refers to from the text | Coreference Resolution | Dialogue | English | English |
task402_grailqa_paraphrase_generation |
Given a question and answer pair, paraphrase the question. | Question Rewriting | Knowledge Base -> Freebase | English | English |
task403_creak_commonsense_inference |
Given a statement and a explanation, judge whether the statement is true based on the explanation | Fact Verification | Wikipedia | English | English |
task404_grailqa_paraphrase_validation |
Given two questions, decide whether the second one is a valid paraphrase of the first one | Text Matching | Knowledge Base -> Freebase | English | English |
task405_narrativeqa_question_generation |
Given a plot summary, create questions that can be answered based on it | Question Generation | Books, Movies | English | English |
task406_mickey_fr_sentence_perturbation_generation |
Given a sentence in French, perform perturbations and generate new sentence in French. | Sentence Perturbation | Commonsense, Knowledge Base -> Wikidata | French | French |
task407_mickey_hi_sentence_perturbation_generation |
Given a sentence in Hindi, perform perturbations and generate new sentence in Hindi. | Sentence Perturbation | Commonsense, Knowledge Base -> Wikidata | Hindi | Hindi |
task408_mickey_it_sentence_perturbation_generation |
Given a sentence in Italian, perform perturbations and generate new sentence in Italian. | Sentence Perturbation | Commonsense, Knowledge Base -> Wikidata | Italian | Italian |
task409_mickey_nl_sentence_perturbation_generation |
Given a sentence in Dutch, perform perturbations and generate new sentence in Dutch. | Sentence Perturbation | Commonsense, Knowledge Base -> Wikidata | Dutch | Dutch |
task410_mickey_ru_sentence_perturbation_generation |
Given a sentence in Russian, perform perturbations and generate new sentence in Russian. | Sentence Perturbation | Commonsense, Knowledge Base -> Wikidata | Russian | Russian |
task411_mickey_vi_sentence_perturbation_generation |
Given a sentence in Vietnamese, perform perturbations and generate new sentence in Vietnamese. | Sentence Perturbation | Commonsense, Knowledge Base -> Wikidata | Vietnamese | Vietnamese |
task412_mickey_zh_sentence_perturbation_generation |
Given a sentence in Chinese, perform perturbations and generate new sentence in Chinese. | Sentence Perturbation | Commonsense, Knowledge Base -> Wikidata | Chinese | Chinese |
task413_mickey_en_sentence_perturbation_generation |
Given a sentence in English, perform perturbations and generate new sentence in English. | Sentence Perturbation | Commonsense, Knowledge Base -> Wikidata | English | English |
task414_mickey_ar_sentence_perturbation_generation |
Given a sentence in Arabic, perform perturbations and generate new sentence in Arabic. | Sentence Perturbation | Commonsense, Knowledge Base -> Wikidata | Arabic | Arabic |
task415_mickey_bg_sentence_perturbation_generation |
Given a sentence in Bulgarian, perform perturbations and generate new sentence in Bulgarian. | Sentence Perturbation | Commonsense, Knowledge Base -> Wikidata | Bulgarian | Bulgarian |
task416_mickey_de_sentence_perturbation_generation |
Given a sentence in German, perform perturbations and generate new sentence in German. | Sentence Perturbation | Commonsense, Knowledge Base -> Wikidata | German | German |
task417_mickey_es_sentence_perturbation_generation |
Given a sentence in Spanish, perform perturbations and generate new sentence in Spanish. | Sentence Perturbation | Commonsense, Knowledge Base -> Wikidata | Spanish | Spanish |
task418_persent_title_generation |
Given a document, generate a short title of the document. | Title Generation | News | English | English |
task419_persent_answer_generation |
Given a document, find the main entity about whom the author is writing. | Named Entity Recognition | News | English | English |
task420_persent_document_sentiment_classification |
Given a document and an entity the task is to select the author's sentiment towards the enity. | Sentiment Analysis | News | English | English |
task421_persent_sentence_sentiment_classification |
Given a sentence and an entity, the task is to select the author's sentiment towards the enity. | Sentiment Analysis | News | English | English |
task422_persent_sentence_sentiment_verification |
Given a sentence, an entity and its sentiment towards the entity, verify if it is the correct sentiment towards the entity. | Sentiment Analysis | News | English | English |
task423_persent_document_sentiment_verification |
Given a document, an entity and its sentiment towards the entity, verify if it is the correct sentiment towards the entity. | Sentiment Analysis | News | English | English |
task424_hindienglish_corpora_hi_en_translation |
Given a Hindi sentence, convert it into English. | Translation | News, TED Talks, Wikipedia | Hindi | English |
task425_hindienglish_corpora_en_hi_translation |
Given an English sentence, convert it into Hindi. | Translation | News, TED Talks, Wikipedia | English | Hindi |
task426_hindienglish_corpora_hi-en_classification |
Given a Hindi sentence and its corresponding English sentence, classify whether it is correct or not. | Text Matching | News, TED Talks, Wikipedia | Hindi, English | English |
task427_hindienglish_corpora_hi-en_language_identification |
Given a sentence, identify whether it is in Hindi or English. | Language Identification | News, TED Talks, Wikipedia | Hindi, English | English |
task428_senteval_inversion |
Given a sentence, judge whether or not two consecutive word have been inverted. | Linguistic Probing | Narrative | English | English |
task429_senteval_tense |
Given a sentence, specify the tense of the main verb. | Linguistic Probing | Narrative | English | English |
task430_senteval_subject_count |
Given a sentence, specify singularity or plurality of the subject. | Linguistic Probing | Narrative | English | English |
task431_senteval_object_count |
Given a sentence, specify singularity or plurality of the object. | Linguistic Probing | Narrative | English | English |
task432_alt_en_hi_translation |
Given an English language sentence translate it into Hindi language. | Translation | Public Places | English | Hindi |
task433_alt_hi_en_translation |
Given an Hindi language sentence translate it into English language. | Translation | Public Places | Hindi | English |
task434_alt_en_hi_answer_generation |
Generate answer yes or no for english and hindi translation pair. | Text Matching | Public Places | English, Hindi | English |
task435_alt_en_ja_translation |
Given an English language sentence translate it into Japanese language. | Translation | Public Places | English | Japanese |
task436_alt_ja_en_translation |
Given an Japanese language sentence translate it into English language. | Translation | Public Places | Japanese | English |
task437_alt_en_ja_answer_generation |
Generate answer yes or no for english and japanese translation pair. | Text Matching | Public Places | Japanese, English | English |
task438_eng_guj_parallel_corpus_en_gu_translation |
Translation from English to Gujarati sentences. | Translation | Captions -> Image Captions | English | Gujarati |
task439_eng_guj_parallel_corpus_gu_en_translation |
Translation from Gujarati to English sentences. | Translation | Captions -> Image Captions | English | Gujarati |
task440_eng_guj_parallel_corpus_gu-en_classification |
Given a sentence in Gujarati and its corresponding English translation, verify that the translation is correct. | Text Matching | Captions -> Image Captions | Gujarati, English | English |
task441_eng_guj_parallel_corpus_gu-en_language_identification |
Given a sentence, identify if it is in the English or Gujarati language. | Language Identification | Captions -> Image Captions | Gujarati, English | English |
task442_com_qa_paraphrase_question_generation |
Generating paraphrases of com_qa questions | Question Rewriting | Web | English | English |
task443_com_qa_ans_question_generation |
Generating questions for com_qa answers | Question Generation | Web | English | English |
task444_com_qa_question_paraphrases_answer_generation |
Generating answers for com_qa question paraphrases | Question Answering | Web | English | English |
task446_opus_paracrawl_en_so_translation |
Translating English text to Somali | Translation | Web | English | Somali |
task447_opus_paracrawl_classification |
Generating the language of the text | Language Identification | Web | French, English, Dutch, Somali, Tagalog | English |
task448_opus_paracrawl_en_tl_translation |
Translating English text to Tagalog | Translation | Web | English | Tagalog |
task449_opus_paracrawl_ig_en_translation |
Translating Igbo text to English | Translation | Web | Igbo | English |
task450_opus_paracrawl_so_en_translation |
Translating Somali text to English | Translation | Web | Somali | English |
task451_opus_paracrawl_tl_en_translation |
Translating Tagalog text to English | Translation | Web | Tagalog | English |
task452_opus_paracrawl_en_ig_translation |
Translating English text to Igbo | Translation | Web | English | Igbo |
task453_swag_answer_generation |
Given a statement context, complete the partial next sentence | Text Completion | Captions -> Video Captions, Story | English | English |
task454_swag_incorrect_answer_generation |
Given a statement context, complete the partial next sentence with incorrect statement | Wrong Candidate Generation | Captions -> Video Captions | English | English |
task455_swag_context_generation |
Given a statement, generate its context or previous statement | Text Completion | Captions -> Video Captions | English | English |
task456_matres_intention_classification |
Given a context and a verb, answer if the given verb is about an intention or not | Information Extraction | News | English | English |
task457_matres_conditional_classification |
Given a context and a verb, answer if the given verb is conditional or not | Word Semantics | News | English | English |
task458_matres_negation_classification |
Given a context and a verb, answer if the given verb is a negation or not | Word Semantics | News | English | English |
task459_matres_static_classification |
Given a context and a verb, answer if the given verb is static or not | Word Semantics | News | English | English |
task460_qasper_answer_generation |
Given a context and a question, answer the question based on the context. | Question Answering | Scientific Research Papers | English | English |
task461_qasper_question_generation |
Given a cotext, generate a question based on it. | Question Generation | Scientific Research Papers | English | English |
task462_qasper_classification |
Given a context and a question, classify the question into abstractive, extractice, or yes-no question | Question Understanding | Scientific Research Papers | English | English |
task463_parsinlu_entailment_classification |
Given a premise sentence and a hypothesis sentence, determine whether the hypothesis sentence entails, contradicts, or is neutral with respect to the given premise sentence | Textual Entailment | Miscellaneous | Persian | English |
task464_parsinlu_entailment_sentence_generation |
Given a premise sentence and a label, generate the hypothesis sentence based on the label and the premise sentence | Textual Entailment | Miscellaneous | Persian | Persian |
task465_parsinlu_qqp_classification |
Given two sentences, determine whether the sentences are paraphrases or not | Text Matching | Miscellaneous | Persian | English |
task466_parsinlu_qqp_text_modification |
Given a sentence, paraphrase it | Paraphrasing | Miscellaneous | Persian | Persian |
task467_parsinlu_rc_answer_generation |
Given a passage and a question, answer the question based on the passage. | Question Answering | Miscellaneous | Persian | Persian |
task468_parsinlu_rc_question_generation |
Given a passage, generate a question based on the passage. | Question Generation | Miscellaneous | Persian | Persian |
task469_mrqa_answer_generation |
Generating answers from MRQA OOD dataset | Question Answering | Wikipedia, News, Natural Science | English | English |
task470_mrqa_question_generation |
Generating question using context passage from MRQA OOD dataset | Question Generation | Wikipedia, News, Natural Science | English | English |
task471_haspart_answer_generation |
Generating entity which is in has-part-relationship with input entity | Entity Generation | Natural Science | English | English |
task472_haspart_classification |
Identifying whether given two entities has in-part-relationship or not. | Entity Relation Classification | Natural Science | English | English |
task473_parsinlu_mc_classification |
Given a question, pick the correct option among a list of multiple candidates. | Question Answering | Miscellaneous | Persian | English |
task474_parsinlu_mc_classification |
Given a question, classify the question based on the required knowledge. | Question Understanding | Miscellaneous | Persian | English |
task475_yelp_polarity_classification |
Classify a given Yelp review to positive or negative sentiment | Sentiment Analysis | Reviews -> Movies | English | English |
task476_cls_english_books_classification |
Classify a given book product review in English to positive or negative sentiment | Sentiment Analysis | Reviews -> Books | English | English |
task477_cls_english_dvd_classification |
Classify a given dvd product review in English to positive or negative sentiment | Sentiment Analysis | Reviews -> Electronics and Grocery | English | English |
task478_cls_english_music_classification |
Classify a given music product review in English to positive or negative sentiment | Sentiment Analysis | Reviews -> Music | English | English |
task479_cls_german_books_classification |
Classify a given book product review in German to positive or negative sentiment | Sentiment Analysis | Reviews -> Books | German | English |
task480_cls_german_dvd_classification |
Classify a given dvd product review in German to positive or negative sentiment | Sentiment Analysis | Reviews -> Electronics and Grocery | German | English |
task481_cls_german_music_classification |
Classify a given music product review in German to positive or negative sentiment | Sentiment Analysis | Reviews -> Music | German | English |
task482_cls_french_books_classification |
Classify a given book product review in French to positive or negative sentiment | Sentiment Analysis | Reviews -> Books | French | English |
task483_cls_french_dvd_classification |
Classify a given dvd product review in French to positive or negative sentiment | Sentiment Analysis | Reviews -> Electronics and Grocery | French | English |
task484_cls_french_music_classification |
Classify a given music product review in French to positive or negative sentiment | Sentiment Analysis | Reviews -> Music | French | English |
task485_cls_japanese_books_classification |
Classify a given book product review in Japanese to positive or negative sentiment | Sentiment Analysis | Reviews -> Books | Japanese | English |
task486_cls_japanese_dvd_classification |
Classify a given dvd product review in Japanese to positive or negative sentiment | Sentiment Analysis | Reviews -> Electronics and Grocery | Japanese | English |
task487_cls_japanese_music_classification |
Classify a given music product review in Japanese to positive or negative sentiment | Sentiment Analysis | Reviews -> Music | Japanese | English |
task488_extract_all_alphabetical_elements_from_list_in_order |
Given a list return all the alphabetical elements from the list in same order as they appear in the list | Program Execution | Code | English | English |
task489_mwsc_question_generation |
Generating questions based on the given sentence | Question Generation | Commonsense | English | English |
task490_mwsc_options_generation |
Generating options to mwsc questions | Question Answering | Commonsense | English | English |
task491_mwsc_answer_generation |
Generating answers to mwsc questions | Question Answering | Commonsense | English | English |
task492_mwsc_incorrect_answer_generation |
Generating incorrect answers to mwsc questions | Wrong Candidate Generation | Commonsense | English | English |
task493_review_polarity_classification |
Classify amazon review into positive or negative | Sentiment Analysis | Reviews -> Electronics and Grocery | English | English |
task494_review_polarity_answer_generation |
Given pair of amazon review and polarity, generate True or False when a review matches polarity | Sentiment Analysis | Reviews -> Electronics and Grocery | English | English |
task495_semeval_headline_classification |
Classify edited news headlines into funny and not funny | Text Categorization | News | English | English |
task496_semeval_answer_generation |
Generate answer yes or no based on given edited sentence and label | Text Categorization | News | English | English |
task497_extract_all_numbers_from_list_in_order |
Given a list return all the numbers from the list in same order as they appear in the list | Program Execution | Code | English | English |
task498_scruples_anecdotes_whoiswrong_classification |
Given a real-life anecdote of a complex ethical situation, identify who is ethically wrong here | Ethics Classification | Commonsense | English | English |
task499_extract_and_add_all_numbers_from_list |
Given a list extract all the numbers from the list and return their sum/addition | Program Execution | Code | English | English |
task500_scruples_anecdotes_title_generation |
Given a real-life anecdote of a complex ethical situation, generate a title that describes the main event/root cause of the situation | Title Generation | Story, Narrative | English | English |
task501_scruples_anecdotes_post_type_verification |
Given a real-life anecdote of a complex ethical situation, verify if the claim about the type of the post is true or not | Text Categorization | Story, Narrative | English | English |
task502_scruples_anecdotes_whoiswrong_verification |
Given a real-life anecdote of a complex ethical situation, verify who is wrong in the situation | Ethics Classification | Story, Narrative | English | English |
task503_scruples_anecdotes_isanswerable |
Given a real-life anecdote of a complex ethical situation, can it be clearly answered, who is ethically wrong here ? | Ethics Classification | Story, Narrative | English | English |
task504_count_all_alphabetical_elements_in_list |
Given a list return the count of all the alphabetical elements from the list | Program Execution | Mathematics | English | English |
task505_count_all_numerical_elements_in_list |
Given a list return the count of all the numerical elements from the list | Program Execution | Mathematics | English | English |
task506_position_of_all_alphabetical_elements_in_list |
Given a list return the position of all the alphabetical elements from the list | Program Execution | Mathematics | English | English |
task507_position_of_all_numerical_elements_in_list |
Given a list return the position of all the numerical elements from the list | Program Execution | Mathematics | English | English |
task508_scruples_dilemmas_more_ethical_isidentifiable |
Given a pair of action statements, can you conclusively identify which statement is less ethical or not ? | Ethics Classification | Story, Narrative | English | English |
task509_collate_of_all_alphabetical_and_numerical_elements_in_list_separately |
Given a list collate all the alphabetical elements at the start of the list followed by all the numerical elements of the list | Program Execution | Mathematics | English | English |
task510_reddit_tifu_title_summarization |
Given the text of a social media post, generate a title summarizing the post | Title Generation | Social Media -> Reddit | English | English |
task511_reddit_tifu_long_text_summarization |
Given the text of a social media post, generate a short summary the post | Summarization | Social Media -> Reddit | English | English |
task512_twitter_emotion_classification |
Given a Twitter post, classify the post's emotion to six classes (sadness, joy, love, anger, fear, surprise) | Sentiment Analysis | Social Media -> Twitter | English | English |
task513_argument_stance_classification |
Given a topic and an argument, decide the stance of the argument towards the topic | Stance Detection | Debatepedia | English | English |
task514_argument_consequence_classification |
Given a topic and an argument, decide whether the argument refers to a consequence of the topic | Text Matching | Debatepedia | English | English |
task515_senteval_odd_word_out |
Given a sentence judge whether a single word has been replaced with another word. | Linguistic Probing | Narrative, Commonsense -> Concepts and Relations | English | English |
task516_senteval_conjoints_inversion |
Given a sentence judge whether two clausal conjoints have been inverted. | Linguistic Probing | Narrative, Commonsense -> Concepts and Relations | English | English |
task517_emo_classify_emotion_of_dialogue |
Classify the emotion of a given dialogue | Sentiment Analysis | Dialogue | English | English |
task518_emo_different_dialogue_emotions |
Given different dialogue determine if they have the same emotion | Sentiment Analysis | Dialogue | English | English |
task519_aquamuse_question_generation |
Given an answer generate a question that would be answered by the answer given | Question Generation | Miscellaneous | English | English |
task520_aquamuse_answer_given_in_passage |
Given a passage and a question determine if the question can be answered by the passage | Answerability Classification | Miscellaneous | English | English |
task521_trivia_question_classification |
Given a text from a trivia quiz, decide the category the question belongs to | Text Categorization | Art, Literature, History, Sociology, Natural Science | English | English |
task522_news_editorial_summary |
Given an article text, select spans of text that show a summary of the thesis of the article. | Summarization | News | English | English |
task523_find_if_numbers_or_alphabets_are_more_in_list |
Given a list find if the count of alphabets is more, less, or same as that of numbers in the list | Program Execution | Mathematics | English | English |
task524_parsinlu_food_aspect_classification |
Given a food review and a question about the reviewer's sentiment toward one aspect of the food, classify the sentiment. | Sentiment Analysis | Reviews -> Food | Persian | English |
task525_parsinlu_movie_aspect_classification |
Given a movie review and a question about the reviewer's sentiment toward one aspect of the movie, classify the sentiment. | Sentiment Analysis | Reviews -> Movies | Persian | English |
task526_parsinlu_movie_overal_classification |
Given a movie review, classify the overal sentiment of the reviewer toward the movie. | Sentiment Analysis | Reviews -> Movies | Persian | English |
task527_parsinlu_food_overal_classification |
Given a food review, classify the overal sentiment of the reviewer toward the food. | Sentiment Analysis | Reviews -> Food | Persian | English |
task528_parsinlu_movie_aspect_detection |
Given a movie review, extract aspects of the movie mentioned in the text. | Information Extraction | Reviews -> Movies | Persian | Persian |
task529_parsinlu_food_aspect_detection |
Given a food review, extract aspects of the food mentioned in the text. | Information Extraction | Reviews -> Food | Persian | Persian |
task530_europarl_en_es_translation |
Given a English sentence, convert it into Spanish. | Translation | Government and Politics | English | Spanish |
task531_europarl_es_en_translation |
Given an Spanish sentence, convert it into English. | Translation | Government and Politics | Spanish | English |
task532_europarl_en-es_classification |
Given a English sentence and its corresponding Spanish translation, classify whether it is correct or not. | Text Matching | Government and Politics | English, Spanish | English |
task533_europarl_es-en_language_identification |
Given a sentence, identify whether it is in English or Spanish. | Language Identification | Government and Politics | English, Spanish | English |
task534_farstail_entailment |
Given two sentences in Persian, choose whether they agree, disagree, neither with each other. | Textual Entailment | History, World Religions | Persian | English |
task535_alt_translation_ch_en |
Language Translate of Dataset Card for ALT from Chinese language to English language while preserving named entities in the original language | Translation | News | Chinese | English |
task536_alt_translation_vi_en |
Language Translate of Dataset Card for ALT from Vietnamese language to English language while preserving named entities in the original language | Translation | News | Vietnamese | English |
task537_alt_translation_th_en |
Language Translate of Dataset Card for ALT from Thai language to English language while preserving named entities in the original language | Translation | News | Thai | English |
task538_alt_translation_bu_en |
Language Translate of Dataset Card for ALT from Burmese language to English language while preserving named entities in the original language | Translation | News | Burmese | English |
task539_alt_translation_ma_en |
Language Translate of Dataset Card for ALT from Malay language to English language while preserving named entities in the original language | Translation | News | Malay | English |
task540_alt_translation_la_en |
Language Translate of Dataset Card for ALT from Laotian language to English language while preserving named entities in the original language | Translation | News | Lao | English |
task541_alt_translation_kh_en |
Language Translate of Dataset Card for ALT from Khmer language to English language while preserving named entities in the original language | Translation | News | Central Khmer | English |
task542_alt_translation_ja_en |
Language Translate of Dataset Card for ALT from Japanese language to English language while preserving named entities in the original language | Translation | News | Japanese | English |
task543_alt_translation_bh_en |
Language Translate of Dataset Card for ALT from Bahasa language to English language while preserving named entities in the original language | Translation | News | Indonesian | English |
task544_alt_translation_hi_en |
Language Translate of Dataset Card for ALT from Hindi language to English language while preserving named entities in the original language | Translation | News | Hindi | English |
task545_alt_translation_fi_en |
Language Translate of Dataset Card for ALT from Filipino language to English language while preserving named entities in the original language | Translation | News | Filipino | English |
task546_alt_translation_bg_en |
Language Translate of Dataset Card for ALT from Bengali language to English language while preserving named entities in the original language | Translation | News | Bengali | English |
task547_alt_translation_entk_en |
Language Translate of Dataset Card for ALT from English Tokens to English language while preserving named entities in the original language | Translation | News | English | English |
task548_alt_translation_en_ch |
Language Translate of Dataset Card for ALT from English language to Chinese language while preserving named entities in the original language | Translation | News | English | Chinese |
task549_alt_translation_en_vi |
Language Translate of Dataset Card for ALT from English language to Vietnamese language while preserving named entities in the original language | Translation | News | English | Vietnamese |
task550_discofuse_sentence_generation |
Senetence Generation on Dataset Card for DISCOFUSE | Sentence Composition | Wikipedia | English | English |
task551_alt_translation_en_th |
Language Translate of Dataset Card for ALT from English language to Thai language while preserving named entities in the original language | Translation | News | English | Thai |
task552_alt_translation_en_bu |
Language Translate of Dataset Card for ALT from English language to Burmese language while preserving named entities in the original language | Translation | News | English | Burmese |
task553_alt_translation_en_ma |
Language Translate of Dataset Card for ALT from English language to Malay language while preserving named entities in the original language | Translation | News | English | Malay |
task554_alt_translation_en_la |
Language Translate of Dataset Card for ALT from English language to Laotian language while preserving named entities in the original language | Translation | News | English | Lao |
task555_alt_translation_en_kh |
Language Translate of Dataset Card for ALT from English language to Khmer language while preserving named entities in the original language | Translation | News | English | Central Khmer |
task556_alt_translation_en_ja |
Language Translate of Dataset Card for ALT from English language to Japanese language while preserving named entities in the original language | Translation | News | English | Japanese |
task557_alt_translation_en_ba |
Language Translate of Dataset Card for ALT from English language to Bahasa language while preserving named entities in the original language | Translation | News | English | Indonesian |
task558_alt_translation_en_hi |
Language Translate of Dataset Card for ALT from English language to Hindi language while preserving named entities in the original language | Translation | News | English | Hindi |
task559_alt_translation_en_fi |
Language Translate of Dataset Card for ALT from English language to Filipino language while preserving named entities in the original language | Translation | News | English | Filipino |
task560_alt_translation_en_entk |
Language Translate of Dataset Card for ALT from English language to English tokens while preserving named entities in the original language | Translation | News | English | English |
task561_alt_translation_en_bg |
Language Translate of Dataset Card for ALT from English language to Bengali language while preserving named entities in the original language | Translation | News | English | Bengali |
task562_alt_language_identification |
Language Identification on Dataset Card for ALT | Language Identification | News | English, Bengali, Filipino, Hindi, Indonesian, Japanese, Central Khmer, Lao, Malay, Burmese, Thai, Vietnamese, Chinese | English |
task563_discofuse_answer_generation |
Answer Generation on Dataset Card for DISCOFUSE | Discourse Connective Identification | Wikipedia | English | English |
task564_discofuse_classification |
Classification on Dataset Card for DISCOFUSE | Discourse Relation Classification | Wikipedia | English | English |
task565_circa_answer_generation |
Given a question generate an answer that is relevant to the question. | Dialogue Generation | Dialogue | English | English |
task566_circa_classification |
Given two sentences, check if they have the same meaning. | Text Matching | Dialogue | English | English |
task567_circa_text_generation |
Given a question, Predict the context of the given question. | Misc. | Dialogue | English | English |
task568_circa_question_generation |
Given an answer, Predict the question. | Question Generation | Dialogue | English | English |
task569_recipe_nlg_text_generation |
Predict the title given its required ingredients and directions. | Title Generation | Food | English | English |
task570_recipe_nlg_ner_generation |
Generate the ner given its required ingredients given. | Named Entity Recognition | Food | English | English |
task571_recipe_nlg_ner_generation |
Generate the ner given its directions. | Named Entity Recognition | Food | English | English |
task572_recipe_nlg_text_generation |
Generate the unknown step by knowing the other steps given in the directions. | Fill in The Blank | Food | English | English |
task573_air_dialogue_classification |
Givena a conversation between a flight 'agent' and the 'customer' classify the goal of the conversation. | Intent Identification | Dialogue | English | English |
task574_air_dialogue_sentence_generation |
Given a conversation between a flight 'agent' and the 'customer', find the missing dialogue in the conversation. | Dialogue Generation | Dialogue | English | English |
task575_air_dialogue_classification |
Classification of the sentence spoken by 'agent' and 'customer'. | Speaker Identification | Dialogue | English | English |
task576_curiosity_dialogs_answer_generation |
Answering multiple choices dialogue act problems. | Dialogue Generation | Dialogue, Commonsense -> Concepts and Relations -> Social Commonsense | English | English |
task577_curiosity_dialogs_classification |
Classification of the sentence spoken by 'assistant' and 'user'. | Speaker Identification | Dialogue, Commonsense -> Concepts and Relations -> Social Commonsense | English | English |
task578_curiosity_dialogs_answer_generation |
Given a conversation between 'assistant' and 'user', generate the most important location in the conversation | Information Extraction | Dialogue, Commonsense -> Concepts and Relations -> Social Commonsense | English | English |
task579_socialiqa_classification |
Given a context, a question and an answer; classify whether the answer is correct or not. | Answer Verification | Commonsense -> Concepts and Relations -> Social Commonsense | English | English |
task580_socialiqa_answer_generation |
Given a context, a question and three options; provide correct answer for the question based on the context. | Question Answering | Commonsense -> Concepts and Relations -> Social Commonsense | English | English |
task581_socialiqa_question_generation |
Generate a question based on the given context and an answer. | Question Generation | Commonsense -> Concepts and Relations -> Social Commonsense | English | English |
task582_naturalquestion_answer_generation |
You are given an open-domain question and return an answer based on factual information | Question Answering | Wikipedia | English | English |
task583_udeps_eng_coarse_pos_tagging |
Given a sentence, a word in that sentence and the position of that word in the sentence, find the parts-of-speech tag of the word | Pos Tagging | News | English | English |
task584_udeps_eng_fine_pos_tagging |
Given a sentence, a word in that sentence and the position of that word in the sentence, find the parts-of-speech tag of the word | Pos Tagging | News | English | English |
task585_preposition_classification |
Given two words, you have to generate which preposition connects both. | Preposition Prediction | Linguistics | English | English |
task586_amazonfood_polarity_classification |
Given a review of an amazon food product, you have to classify if the review is positive or negative. | Sentiment Analysis | Reviews -> Food | English | English |
task587_amazonfood_polarity_correction_classification |
Given a review of amazon food products and it's polarity, you have to classify whether the polarity is correct or not. | Sentiment Analysis | Reviews -> Food | English | English |
task588_amazonfood_rating_classification |
Given a review of amazon food products, you have to classify the rating out of 5. | Sentiment Analysis | Reviews -> Food | English | English |
task589_amazonfood_summary_text_generation |
Given a review of amazon's food product, you have to generate the summary of the review. | Summarization | Reviews -> Food | English | English |
task590_amazonfood_summary_correction_classification |
Given a review of amazon's food product and its summary, you have to classify whether the summary is correct or not. | Text Matching | Reviews -> Food | English | English |
task591_sciq_answer_generation |
Given a scientific question, generate a correct answer to the given question | Question Answering | Natural Science -> School Science Textbooks | English | English |
task592_sciq_incorrect_answer_generation |
Given a scientific question, generate an incorrect answer to the given question | Wrong Candidate Generation | Natural Science -> School Science Textbooks | English | English |
task593_sciq_explanation_generation |
Given a scientific question and its correct answer, generate supporting facts for the answer. | Explanation | Natural Science -> School Science Textbooks | English | English |
task594_sciq_question_generation |
Given a scientific passage and an answer, generate a question for the given answer. | Question Generation | Natural Science -> School Science Textbooks | English | English |
task595_mocha_answer_generation |
Generating answers to MOCHA questions | Question Answering | Wikipedia, Books, Movies, Story, History | English | English |
task596_mocha_question_generation |
Generating questions based on MOCHA | Question Answering | Wikipedia, Books, Movies, Story, History | English | English |
task597_cuad_answer_generation |
Generating answers to CUAD questions | Question Answering | Law | English | English |
task598_cuad_answer_generation |
Generating starting index of the answers to CUAD questions | Question Answering | Law | English | English |
task599_cuad_question_generation |
Generating questions based on CUAD | Question Generation | Law | English | English |
task600_find_the_longest_common_substring_in_two_strings |
Given two strings return the longest common substring in those two strings | Program Execution | Mathematics | English | English |
task601_flores_translation_sntoen |
Translating the text from sinhali to english | Translation | Miscellaneous | Sinhala | English |
task602_wikitext-103_answer_generation |
Generate title for the given passage | Title Generation | Wikipedia | English | English |
task603_wikitext-103_fill_in_the_blank |
Filling the blanks in the given passage text | Fill in The Blank | Wikipedia | English | English |
task604_flores_translation_entosn |
Translating the text from english to sinhali | Translation | Miscellaneous | English | Sinhala |
task605_find_the_longest_common_subsequence_in_two_lists |
Given two lists return the longest common subsequence in those two lists | Program Execution | Mathematics | English | English |
task606_sum_of_all_numbers_in_list_between_positions_i_and_j |
Given a list extract and then return sum of all the numbers between two positions i and j | Program Execution | Mathematics | English | English |
task607_sbic_intentional_offense_binary_classification |
Determine whether the post is intentionally offensive or not | Toxic Language Detection | Social Media -> Twitter | English | English |
task608_sbic_sexual_offense_binary_classification |
Determine whether the post is sexually offensive/explicit or not | Toxic Language Detection | Social Media -> Twitter | English | English |
task609_sbic_potentially_offense_binary_classification |
Determine whether the post is potentially offensive or not | Toxic Language Detection | Social Media -> Twitter | English | English |
task610_conllpp_ner |
Recognize and label proper nouns (Named Entity Recognition) | Named Entity Recognition | Miscellaneous | English | English |
task611_mutual_multi_turn_dialogue |
Given a conversation between two people and 4 options on how the conversation should continue, choose the most reasonable option | Dialogue Generation | Dialogue | English | English |
task612_yorubabbc_classification |
Given a news article headline from Yoruba BBC, classify the label of the headline. | Text Categorization | News | Yoruba | English |
task613_politifact_text_generation |
Given a statement from a politifact.com you task is to generate the subject of discussion of the statement. | Keyword Tagging | Government and Politics | English | English |
task614_glucose_cause_event_detection |
Given a story and a selected sentence, find an event in the story that caused that sentence | Cause Effect Classification | Story | English | English |
task615_moviesqa_answer_generation |
Given a question from an open movie database, generate an answer for that. | Question Answering | Movies | English | English |
task616_cola_classification |
Given a sentence you have to return if it is acceptable or unacceptable. | Text Quality Evaluation | Linguistics | English | English |
task617_amazonreview_category_text_generation |
Given an Amazon product review your task is to generate the category of product. | Text Categorization | Reviews | English | English |
task618_amazonreview_summary_text_generation |
Given an Amazon product review your task is to generate the summary of the review. | Summarization | Reviews | English | English |
task619_ohsumed_abstract_title_generation |
Generating title to Ohsumed dataset abstracts | Title Generation | Reviews | English | English |
task620_ohsumed_medical_subject_headings_answer_generation |
Generating MESH terms to Ohsumed dataset abstracts | Keyword Tagging | Scientific Research Papers | English | English |
task621_ohsumed_yes_no_numerical_answer_generation |
Generating Yes/No answer to Ohsumed dataset questions | Information Extraction | Scientific Research Papers | English | English |
task622_replace_alphabets_in_a_list_by_their_position_in_english_alphabet |
Given a list replace all the alphabets in it with their position in the English Alphabet | Program Execution | Mathematics | English | English |
task623_ohsumed_yes_no_answer_generation |
Generating Yes/No answers to Ohsumed dataset questions | Keyword Tagging | Scientific Research Papers | English | English |
task624_ohsumed_question_answering |
Given a abstract and question, select the best answer from the given choices. | Text Matching | Scientific Research Papers | English | English |
task625_xlwic_true_or_false_answer_generation |
Determine whether both the sentences use the aforementioned word with the same meaning | Word Semantics | Miscellaneous | English | English |
task626_xlwic_sentence_based_on_given_word_sentence_generation |
Generating a sentence from a given word | Sentence Composition | Miscellaneous | English | English |
task627_xlwic_word_with_same_meaning_sentence_generation |
Generating a sentence using a given word and sentence where the word is used with the same meaning as in the given sentence | Sentence Composition | Miscellaneous | English | English |
task628_xlwic_word_with_different_meaning_sentence_generation |
Generating a sentence using a given word and sentence where the word is used with a different meaning than in the given sentence | Sentence Composition | Miscellaneous | English | English |
task629_dbpedia_14_classification |
Classifying the topic names of the text (dbpedia_14 dataset) | Text Categorization | Wikipedia | English | English |
task630_dbpedia_14_classification |
Verfying if the title of the text is correct(dbpedia_14 dataset) | Text Matching | Wikipedia | English | English |
task631_dbpedia_14_incorrect_answer_generation |
Generating incorrect answers from specified categories | Wrong Candidate Generation | Wikipedia | English | English |
task632_dbpedia_14_classification |
Verifying if the text is about a person (dbpedia_14 dataset) | Text Categorization | Wikipedia | English | English |
task633_dbpedia_14_answer_generation |
Generating answer to question ((dbpedia_14 dataset)) | Text Categorization | Wikipedia | English | English |
task634_allegro_reviews_classification |
Classify the given product review to specified categories | Sentiment Analysis | Reviews | Polish, English | English |
task635_allegro_reviews_answer_generation |
Generating "yes" or "no" to question whether the review is a positive review | Sentiment Analysis | Reviews | Polish, English | English |
task636_extract_and_sort_unique_alphabets_in_a_list |
Given a list extract all the unique alphabets from it and sort them alphabetically | Program Execution | Mathematics | English | English |
task637_extract_and_sort_unique_digits_in_a_list |
Given a list extract all the unique digits used in the number in it and sort them in ascending order | Program Execution | Mathematics | English | English |
task638_multi_woz_classification |
Classifying dialouge into User and System | Speaker Identification | Dialogue | English | English |
task639_multi_woz_user_utterance_generation |
Generate a User utterance when System's reply is given | Dialogue Generation | Dialogue | English | English |
task640_esnli_classification |
Given a premise and hypothesis, determine if the hypothesis entails, contradicts, or is neutral to the premise. | Textual Entailment | Miscellaneous | English | English |
task641_esnli_classification |
Classification based on if two sentences agree, disasgree, or neutral. | Textual Entailment | Miscellaneous | English | English |
task642_esnli_classification |
Classification based on if two statements agree/disagree or can't be determined. | Textual Entailment | Miscellaneous | English | English |
task643_refresd_classification |
Classification based on if an english and french sentence are different or equivalent. | Text Matching | Miscellaneous | English, French | English |
task644_refresd_translation |
Translation from english to french sentences. | Translation | Miscellaneous | English | French |
task645_summarization |
Generating summary for Data | Keyword Tagging | Wikipedia | English | English |
task646_answer_generation |
Find pronoun from the sentence | Information Extraction | Narrative | English | English |
task647_answer_generation |
Pronoun Quote Finder | Information Extraction | Narrative | English | English |
task648_answer_generation |
Find subject to the pronoun in the sentence | Coreference Resolution | Narrative | English | English |
task649_race_blank_question_generation |
Generate a fill-in-the-blank question based on the given article and an answer. | Question Generation | English Exams | English | English |
task650_opus100_ar_en_translation |
Given an Arabic sentence, translate it into English. | Translation | Dialogue | Arabic | English |
task651_opus100_en_ar_translation |
Given an English sentence, translate it into Arabic. | Translation | Dialogue | English | Arabic |
task652_parsinlu_en_fa_translation |
Given an English question, translate it into Persian. | Translation | Web | English | Persian |
task653_parsinlu_fa_en_translation |
Given a Persian question, translate it into English. | Translation | Web | Persian | English |
task654_bible_fa_en_translation |
Given a Persian sentence from the Bible, translate it into English. | Translation | World Religions, Books | Persian | English |
task655_bible_en_fa_translation |
Given an English sentence from the Bible, translate it into Persian. | Translation | World Religions, Books | English | Persian |
task656_quran_en_fa_translation |
Given an English sentence from the Quran, translate it into Persian. | Translation | World Religions, Books | English | Persian |
task657_quran_fa_en_translation |
Given a Persian sentence from the Quran, translate it into English. | Translation | World Religions, Books | Persian | English |
task658_tep_en_fa_translation |
Given an English sentence, translate it into Persian. | Translation | Miscellaneous | English | Persian |
task659_tep_fa_en_translation |
Given a Persian sentence, translate it into English. | Translation | Miscellaneous | Persian | English |
task660_mizan_fa_en_translation |
Given a Persian sentence, translate it into English. | Translation | Miscellaneous | Persian | English |
task661_mizan_en_fa_translation |
Given an English sentence, translate it into Persian. | Translation | Miscellaneous | English | Persian |
task662_global_voices_fa_en_translation |
Given a Persian sentence, translate it into English. | Translation | News | Persian | English |
task663_global_voices_en_fa_translation |
Given an English sentence, translate it into Persian. | Translation | News | English | Persian |
task664_mmmlu_answer_generation_abstract_algebra |
Answering mutlitple choice questions on abstract algebra | Question Answering | Mathematics | English | English |
task665_mmmlu_answer_generation_anatomy |
Answering mutlitple choice questions on anatomy | Question Answering | Biology -> Anatomy | English | English |
task666_mmmlu_answer_generation_astronomy |
Answering mutlitple choice questions on astronomy | Question Answering | Astronomy | English | English |
task667_mmmlu_answer_generation_business_ethics |
Answering mutlitple choice questions on business ethics | Question Answering | Business Ethics | English | English |
task668_extreme_abstract_summarization |
Generate a summary of this abstract. | Summarization | Scientific Research Papers | English | English |
task669_ambigqa_answer_generation |
Given an open-domain, provide an answer for that question. | Question Answering | Wikipedia | English | English |
task670_ambigqa_question_generation |
Given an ambiguous question, return a question which clarifies the given question. | Question Rewriting | Wikipedia | English | English |
task671_ambigqa_text_generation |
Given an ambiguous question, provide one clarifying question and answer for the generated question. | Question Rewriting | Wikipedia | English | English |
task672_nummersense |
Given a cloze question, identify the missing numerical value | Fill in The Blank | Commonsense | English | English |
task672_amazon_and_yelp_summarization_dataset_summarization |
Generating summaries to amazon/yelp reviews | Summarization | Reviews | English | English |
task673_google_wellformed_query_classification |
Given a query, classify whether it's a good or bad query | Question Understanding | Miscellaneous | English | English |
task674_google_wellformed_query_sentence_generation |
Given a set of queries, find out the query which is not well-formed | Text Quality Evaluation | Miscellaneous | English | English |
task675_google_wellformed_query_sentence_generation |
Given a set of queries, find out the query which is well-formed | Text Quality Evaluation | Miscellaneous | English | English |
task676_ollie_relationship_answer_generation |
Generating relationship based on given inputs in Ollie dataset | Information Extraction | Narrative | English | English |
task677_ollie_sentence_answer_generation |
Generating sentences based on given inputs in Ollie dataset | Data to Text | Narrative | English | English |
task678_ollie_actual_relationship_answer_generation |
Generating the exact form of relationship based on given inputs in Ollie dataset | Information Extraction | Narrative | English | English |
task679_hope_edi_english_text_classification |
Classify text in english from Hope EDI dataset | Text Categorization | Social Media | English | English |
task680_hope_edi_tamil_text_classification |
Classify text in tamil from Hope EDI dataset | Text Categorization | Social Media | Tamil | English |
task681_hope_edi_malayalam_text_classification |
Classify text in malayalam from Hope EDI dataset | Text Categorization | Social Media | English | English |
task682_online_privacy_policy_text_classification |
Classify privacy policy texts from OPP-115 Dataset | Text Categorization | Social Media | English | English |
task683_online_privacy_policy_text_purpose_answer_generation |
Generate the purpose of privacy policy texts from OPP-115 Dataset | Information Extraction | Law | English | English |
task684_online_privacy_policy_text_information_type_generation |
Generate the type of information used by website, mentioned in privacy policy texts from OPP-115 Dataset | Information Extraction | Law | English | English |
task685_mmmlu_answer_generation_clinical_knowledge |
Answering mutlitple choice questions on clinical knowledge | Question Answering | Biology -> Clinical Knowledge | English | English |
task686_mmmlu_answer_generation_college_biology |
Answering mutlitple choice questions on college biology | Question Answering | Biology | English | English |
task687_mmmlu_answer_generation_college_chemistry |
Answering mutlitple choice questions on college chemistry | Question Answering | Chemistry | English | English |
task688_mmmlu_answer_generation_college_computer_science |
Answering mutlitple choice questions on college computer science | Question Answering | Computer Science | English | English |
task689_mmmlu_answer_generation_college_mathematics |
Answering mutlitple choice questions on college mathematics | Question Answering | Mathematics | English | English |
task690_mmmlu_answer_generation_college_medicine |
Answering mutlitple choice questions on college medicine | Question Answering | Medicine | English | English |
task691_mmmlu_answer_generation_college_physics |
Answering mutlitple choice questions on college physics | Question Answering | Physics | English | English |
task692_mmmlu_answer_generation_computer_security |
Answering mutlitple choice questions on computer security | Question Answering | Computer Science -> Computer Security | English | English |
task693_mmmlu_answer_generation_conceptual_physics |
Answering mutlitple choice questions on conceptual physics | Question Answering | Physics | English | English |
task694_mmmlu_answer_generation_econometrics |
Answering mutlitple choice questions on econometrics | Question Answering | Econometrics | English | English |
task695_mmmlu_answer_generation_electrical_engineering |
Answering mutlitple choice questions on electrical engineering | Question Answering | Electrical Engineering | English | English |
task696_mmmlu_answer_generation_elementary_mathematics |
Answering mutlitple choice questions on elementary mathematics | Question Answering | Mathematics | English | English |
task697_mmmlu_answer_generation_formal_logic |
Answering mutlitple choice questions on formal logic | Question Answering | Logic -> Formal logic | English | English |
task698_mmmlu_answer_generation_global_facts |
Answering mutlitple choice questions on global facts | Question Answering | Global Facts | English | English |
task699_mmmlu_answer_generation_high_school_biology |
Answering mutlitple choice questions on high school biology | Question Answering | Biology | English | English |
task700_mmmlu_answer_generation_high_school_chemistry |
Answering mutlitple choice questions on high school chemistry | Question Answering | Chemistry | English | English |
task701_mmmlu_answer_generation_high_school_computer_science |
Answering mutlitple choice questions on high school computer science | Question Answering | Computer Science | English | English |
task702_mmmlu_answer_generation_high_school_european_history |
Answering mutlitple choice questions on high school european history | Question Answering | History -> European History | English | English |
task703_mmmlu_answer_generation_high_school_geography |
Answering mutlitple choice questions on high school geography | Question Answering | Geography | English | English |
task704_mmmlu_answer_generation_high_school_government_and_politics |
Answering mutlitple choice questions on high school government and politics | Question Answering | Government and Politics | English | English |
task705_mmmlu_answer_generation_high_school_macroeconomics |
Answering mutlitple choice questions on high school macroeconomics | Question Answering | Economics -> Macroeconomics | English | English |
task706_mmmlu_answer_generation_high_school_mathematics |
Answering mutlitple choice questions on high school mathematics | Question Answering | Mathematics | English | English |
task707_mmmlu_answer_generation_high_school_microeconomics |
Answering mutlitple choice questions on high school microeconomics | Question Answering | Economics -> Microeconomics | English | English |
task708_mmmlu_answer_generation_high_school_physics |
Answering mutlitple choice questions on high school physics | Question Answering | Physics | English | English |
task709_mmmlu_answer_generation_high_school_psychology |
Answering mutlitple choice questions on high school psychology | Question Answering | Psychology | English | English |
task710_mmmlu_answer_generation_high_school_statistics |
Answering mutlitple choice questions on high school statistics | Question Answering | Statistics | English | English |
task711_mmmlu_answer_generation_high_school_us_history |
Answering mutlitple choice questions on high school us history | Question Answering | History | English | English |
task712_mmmlu_answer_generation_high_school_world_history |
Answering mutlitple choice questions on high school world history | Question Answering | History | English | English |
task713_mmmlu_answer_generation_human_aging |
Answering mutlitple choice questions on human aging | Question Answering | Biology -> Human Biology | English | English |
task714_mmmlu_answer_generation_human_sexuality |
Answering mutlitple choice questions on human sexuality | Question Answering | Human Sexuality | English | English |
task715_mmmlu_answer_generation_international_law |
Answering mutlitple choice questions on international law | Question Answering | International Law | English | English |
task716_mmmlu_answer_generation_jurisprudence |
Answering mutlitple choice questions on jurisprudence | Question Answering | Jurisprudence | English | English |
task717_mmmlu_answer_generation_logical_fallacies |
Answering mutlitple choice questions on logical fallacies | Question Answering | Formal Fallacy | English | English |
task718_mmmlu_answer_generation_machine_learning |
Answering mutlitple choice questions on machine learning | Question Answering | Computer Science -> Machine Learning | English | English |
task719_mmmlu_answer_generation_management |
Answering mutlitple choice questions on management | Question Answering | Management | English | English |
task720_mmmlu_answer_generation_marketing |
Answering mutlitple choice questions on marketing | Question Answering | Marketing | English | English |
task721_mmmlu_answer_generation_medical_genetics |
Answering mutlitple choice questions on medical genetics | Question Answering | Medical Genetics | English | English |
task722_mmmlu_answer_generation_random_topic |
Answering mutlitple choice questions on miscellaneous | Question Answering | Miscellaneous | English | English |
task723_mmmlu_answer_generation_moral_disputes |
Answering mutlitple choice questions on moral disputes | Question Answering | Moral Scenarios | English | English |
task724_mmmlu_answer_generation_moral_scenarios |
Answering mutlitple choice questions on moral scenarios | Question Answering | Moral Scenarios | English | English |
task725_mmmlu_answer_generation_nutrition |
Answering mutlitple choice questions on nutrition | Question Answering | Nutrition | English | English |
task726_mmmlu_answer_generation_philosophy |
Answering mutlitple choice questions on philosophy | Question Answering | Philosophy | English | English |
task727_mmmlu_answer_generation_prehistory |
Answering mutlitple choice questions on prehistory | Question Answering | Prehistory | English | English |
task728_mmmlu_answer_generation_professional_accounting |
Answering mutlitple choice questions on professional accounting | Question Answering | Accounting | English | English |
task729_mmmlu_answer_generation_professional_law |
Answering mutlitple choice questions on professional law | Question Answering | Law | English | English |
task730_mmmlu_answer_generation_professional_medicine |
Answering mutlitple choice questions on professional medicine | Question Answering | Medicine | English | English |
task731_mmmlu_answer_generation_professional_psychology |
Answering mutlitple choice questions on professional psychology | Question Answering | Psychology | English | English |
task732_mmmlu_answer_generation_public_relations |
Answering mutlitple choice questions on public relations | Question Answering | Public Relations | English | English |
task733_mmmlu_answer_generation_security_studies |
Answering mutlitple choice questions on security studies | Question Answering | Security: National Security | English | English |
task734_mmmlu_answer_generation_sociology |
Answering mutlitple choice questions on sociology | Question Answering | Sociology | English | English |
task735_mmmlu_answer_generation_us_foreign_policy |
Answering mutlitple choice questions on us foreign policy | Question Answering | US Foreign Policy | English | English |
task736_mmmlu_answer_generation_virology |
Answering mutlitple choice questions on virology | Question Answering | Biology -> Virology | English | English |
task737_mmmlu_answer_generation_world_religions |
Answering mutlitple choice questions on world religions | Question Answering | World Religions | English | English |
task738_perspectrum_classification |
Decide whether the given perspective supports or undermines the given claim. | Textual Entailment | Debatepedia | English | English |
task739_lhoestq_question_generation |
Given a passage, generate an appropriate question based on the passage. | Question Generation | Web | English | English |
task740_lhoestq_answer_generation_quantity |
Given a passage and a question, answer the question based on the passage to output a numerical value. | Question Answering | Web | English | English |
task741_lhoestq_answer_generation_place |
Given a passage and a question, answer the question based on the passage to output a particular place or position of something. | Question Answering | Web | English | English |
task742_lhoestq_answer_generation_frequency |
Given a passage and a question, answer the question based on the passage to output the frequency with which some things occur. | Question Answering | Web | English | English |
task743_eurlex_summarization |
Generate headline (summary) for legal act article | Title Generation | Law | English | English |
task744_eurlex_classification |
Identify the legal act article whether it is Regulation, Decision or Directive | Text Categorization | Law | English | English |
task745_ai2_arithmetic_questions_arithmetic |
Given an arithmetic question, compute a solution | Question Answering | Mathematics | English | English |
task746_yelp_restaurant_review_classification |
Restaurant review classification based on its sentiment (i.e., positive or negative) | Sentiment Analysis | Reviews | English | English |
task747_glucose_cause_emotion_detection |
Given a story and a selected sentence, find an emotion or human drive in the story that caused that sentence | Information Extraction | Story | English | English |
task748_glucose_reverse_cause_event_detection |
Given a story and a selected sentence, find an event that is directly caused or made possible by that sentence | Information Extraction | Story | English | English |
task749_glucose_reverse_cause_emotion_detection |
Given a story and a selected sentence, find an emotion or a human drive that is directly caused or made possible by that sentence | Information Extraction | Story | English | English |
task750_aqua_multiple_choice_answering |
Given a mathematical question , find the most suitable numerical answer | Question Answering | Mathematics | English | English |
task751_svamp_subtraction_question_answering |
Given a mathematical question involving subtraction, find the most suitable numerical answer | Question Answering | Mathematics | English | English |
task752_svamp_multiplication_question_answering |
Given a mathematical question involving multiplication, find the most suitable numerical answer | Question Answering | Mathematics | English | English |
task753_svamp_addition_question_answering |
Given a mathematical question involving addition , find the most suitable numerical answer | Question Answering | Mathematics | English | English |
task754_svamp_common-division_question_answering |
Given a mathematical question involving division, find the most suitable numerical answer | Question Answering | Mathematics | English | English |
task755_find_longest_substring_and_replace_its_sorted_lowercase_version_in_both_lists |
Given two strings find the longest common substring in the strings, then convert it to all lowercase, and sort it alphabetically, and finally place it back at the same position in the two lists | Program Execution | Mathematics | English | English |
task756_find_longert_substring_and_return_all_unique_alphabets_in_it |
Given two strings find the longer of the two, then lowercase it and return all unique alphabets in it | Program Execution | Mathematics | English | English |
task757_msr_sqa_question_generation |
Given a table from msr_sqa dataset, generate a question based on the information presented | Question Generation | Sports, Statistics, News | English | English |
task758_msr_sqa_question_answer_generation |
Given a table from msr_sqa dataset and a question based on that table, generate a correct answer based on the table | Question Answering | Sports, Statistics, News | English | English |
task759_msr_sqa_incorrect_answer_generation |
Given a table from msr_sqa dataset and a question based on that table, generate an incorrect correct answer based on the table | Wrong Candidate Generation | Sports, Statistics, News | English | English |
task760_msr_sqa_long_text_generation |
Given a table from msr_sqa dataset, generate a long text passage based on the information in the tabular data | Data to Text | Sports, Statistics, News | English | English |
task761_app_review_classification |
Given an app review, classify whether it's Positive or Negative | Sentiment Analysis | Reviews | English | English |
task762_emea_fr_sk_translation |
Translate French sentences to Slovak while preserving named entities in the original language | Translation | Miscellaneous | French | Slovak |
task763_emea_es_lt_translation |
Translate Spanish sentences to Lithuanian while preserving named entities in the original language | Translation | Miscellaneous | Spanish | Lithuanian |
task764_emea_bg_el_classification |
Identify whether translated sentence is Greek or not. | Text Matching | Miscellaneous | Bulgarian | English |
task765_emea_bg_el_translation |
Translate Bulgarian sentences to Greek while preserving named entities in the original language | Translation | Miscellaneous | Bulgarian | Greek |
task766_craigslist_bargains_classification |
Classifying items in Craigslist Bargains | Dialogue State Tracking | Dialogue | English | English |
task767_craigslist_bargains_classification |
Classifying offer type in Craigslist Bargains | Text Categorization | Dialogue | English | English |
task768_qed_text_span_selection |
Selecting one word answers from the span of a sentence from a passage to answer questions | Question Answering | Wikipedia | English | English |
task769_qed_summarization |
Generating titles for passage | Title Generation | Wikipedia | English | English |
task770_pawsx_english_text_modification |
Given a sentence in English, provide an equivalent paraphrase in said language | Paraphrasing | Wikipedia | English | English |
task771_pawsx_korean_text_modification |
Given a sentence in Korean, provide an equivalent paraphrase in said language | Paraphrasing | Wikipedia | Korean | Korean |
task772_pawsx_french_text_modification |
Given a sentence in French, provide an equivalent paraphrase in said language | Paraphrasing | Wikipedia | French | French |
task773_pawsx_spanish_text_modification |
Given a sentence in Spanish, provide an equivalent paraphrase in said language | Paraphrasing | Wikipedia | Spanish | Spanish |
task774_pawsx_german_text_modification |
Given a sentence in German, provide an equivalent paraphrase in said language | Paraphrasing | Wikipedia | German | German |
task775_pawsx_chinese_text_modification |
Given a sentence in Chinese, provide an equivalent paraphrase in said language | Paraphrasing | Wikipedia | Chinese | Chinese |
task776_pawsx_japanese_text_modification |
Given a sentence in Japanese, provide an equivalent paraphrase in said language | Paraphrasing | Wikipedia | Japanese | Japanese |
task777_pawsx_english_korean_translation |
Given a sentence in English, provide an equivalent translation to Korean | Translation | Wikipedia | English | Korean |
task778_pawsx_english_french_translation |
Given a sentence in English, provide an equivalent translation to French | Translation | Wikipedia | English | French |
task779_pawsx_english_spanish_translation |
Given a sentence in English, provide an equivalent translation to Spanish | Translation | Wikipedia | English | Spanish |
task780_pawsx_english_german_translation |
Given a sentence in English, provide an equivalent translation to German | Translation | Wikipedia | English | German |
task781_pawsx_english_chinese_translation |
Given a sentence in English, provide an equivalent translation to Chinese | Translation | Wikipedia | English | Chinese |
task782_pawsx_english_japanese_translation |
Given a sentence in English, provide an equivalent translation to Japanese | Translation | Wikipedia | English | Japanese |
task783_pawsx_korean_english_translation |
Given a sentence in Korean, provide an equivalent translation to English | Translation | Wikipedia | Korean | English |
task784_pawsx_korean_french_translation |
Given a sentence in Korean, provide an equivalent translation to French | Translation | Wikipedia | Korean | French |
task785_pawsx_korean_spanish_translation |
Given a sentence in Korean, provide an equivalent translation to Spanish | Translation | Wikipedia | Korean | Spanish |
task786_pawsx_korean_german_translation |
Given a sentence in Korean, provide an equivalent translation to German | Translation | Wikipedia | Korean | German |
task787_pawsx_korean_chinese_translation |
Given a sentence in Korean, provide an equivalent translation to Chinese | Translation | Wikipedia | Korean | Chinese |
task788_pawsx_korean_japanese_translation |
Given a sentence in Korean, provide an equivalent translation to Japanese | Translation | Wikipedia | Korean | Japanese |
task789_pawsx_french_english_translation |
Given a sentence in French, provide an equivalent translation to English | Translation | Wikipedia | French | English |
task790_pawsx_french_korean_translation |
Given a sentence in French, provide an equivalent translation to Korean | Translation | Wikipedia | French | Korean |
task791_pawsx_french_spanish_translation |
Given a sentence in French, provide an equivalent translation to Spanish | Translation | Wikipedia | French | Spanish |
task792_pawsx_french_german_translation |
Given a sentence in French, provide an equivalent translation to German | Translation | Wikipedia | French | German |
task793_pawsx_french_chinese_translation |
Given a sentence in French, provide an equivalent translation to Chinese | Translation | Wikipedia | French | Chinese |
task794_pawsx_french_japanese_translation |
Given a sentence in French, provide an equivalent translation to Japanese | Translation | Wikipedia | French | Japanese |
task795_pawsx_spanish_english_translation |
Given a sentence in Spanish, provide an equivalent translation to English | Translation | Wikipedia | Spanish | English |
task796_pawsx_spanish_korean_translation |
Given a sentence in Spanish, provide an equivalent translation to Korean | Translation | Wikipedia | Spanish | Korean |
task797_pawsx_spanish_french_translation |
Given a sentence in Spanish, provide an equivalent translation to French | Translation | Wikipedia | Spanish | French |
task798_pawsx_spanish_german_translation |
Given a sentence in Spanish, provide an equivalent translation to German | Translation | Wikipedia | Spanish | German |
task799_pawsx_spanish_chinese_translation |
Given a sentence in Spanish, provide an equivalent translation to Chinese | Translation | Wikipedia | Spanish | Chinese |
task800_pawsx_spanish_japanese_translation |
Given a sentence in Spanish, provide an equivalent translation to Japanese | Translation | Wikipedia | Spanish | Japanese |
task801_pawsx_german_english_translation |
Given a sentence in German, provide an equivalent translation to English | Translation | Wikipedia | German | English |
task802_pawsx_german_korean_translation |
Given a sentence in German, provide an equivalent translation to Korean | Translation | Wikipedia | German | Korean |
task803_pawsx_german_french_translation |
Given a sentence in German, provide an equivalent translation to French | Translation | Wikipedia | German | French |
task804_pawsx_german_spanish_translation |
Given a sentence in German, provide an equivalent translation to Spanish | Translation | Wikipedia | German | Spanish |
task805_pawsx_german_chinese_translation |
Given a sentence in German, provide an equivalent translation to Chinese | Translation | Wikipedia | German | Chinese |
task806_pawsx_german_japanese_translation |
Given a sentence in German, provide an equivalent translation to Japanese | Translation | Wikipedia | German | Japanese |
task807_pawsx_chinese_english_translation |
Given a sentence in Chinese, provide an equivalent translation to English | Translation | Wikipedia | Chinese | English |
task808_pawsx_chinese_korean_translation |
Given a sentence in Chinese, provide an equivalent translation to Korean | Translation | Wikipedia | Chinese | Korean |
task809_pawsx_chinese_french_translation |
Given a sentence in Chinese, provide an equivalent translation to French | Translation | Wikipedia | Chinese | French |
task810_pawsx_chinese_spanish_translation |
Given a sentence in Chinese, provide an equivalent translation to Spanish | Translation | Wikipedia | Chinese | Spanish |
task811_pawsx_chinese_german_translation |
Given a sentence in Chinese, provide an equivalent translation to German | Translation | Wikipedia | Chinese | German |
task812_pawsx_chinese_japanese_translation |
Given a sentence in Chinese, provide an equivalent translation to Japanese | Translation | Wikipedia | Chinese | Japanese |
task813_pawsx_japanese_english_translation |
Given a sentence in Japanese, provide an equivalent translation to English | Translation | Wikipedia | Japanese | English |
task814_pawsx_japanese_korean_translation |
Given a sentence in Japanese, provide an equivalent translation to Korean | Translation | Wikipedia | Japanese | Korean |
task815_pawsx_japanese_french_translation |
Given a sentence in Japanese, provide an equivalent translation to French | Translation | Wikipedia | Japanese | French |
task816_pawsx_japanese_spanish_translation |
Given a sentence in Japanese, provide an equivalent translation to Spanish | Translation | Wikipedia | Japanese | Spanish |
task817_pawsx_japanese_german_translation |
Given a sentence in Japanese, provide an equivalent translation to German | Translation | Wikipedia | Japanese | German |
task818_pawsx_japanese_chinese_translation |
Given a sentence in Japanese, provide an equivalent translation to Chinese | Translation | Wikipedia | Japanese | Chinese |
task819_pec_sentiment_classification |
Given a contextual post, classify the post as holding positive or negative sentiment | Sentiment Analysis | Social Media -> Reddit | English | English |
task820_protoqa_answer_generation |
Given a question, generate a relevant answer to the question | Question Answering | Web | English | English |
task821_protoqa_question_generation |
Given a group of answers, generate a question for all answers | Question Generation | Web | English | English |
task823_peixian-rtgender_sentiment_analysis |
Analyze the sentiment of responses under posters from social media | Sentiment Analysis | Social Media | English | English |
task827_copa_commonsense_reasoning |
Given a premise and two alternative, select the alternative that more plausibly has a causal relation with the premise | Cause Effect Classification | Narrative | English | English |
task828_copa_commonsense_cause_effect |
Given a pair of sentences, judge whether the second sentence is the cause or effect of the first on. | Cause Effect Classification | Narrative | English | English |
task829_giga_fren_translation |
Translation from English language to French language | Translation | Miscellaneous | English | French |
task830_poleval2019_mt_translation |
Translation from English language to Polish language | Translation | Miscellaneous | English | Polish |
task831_giga_fren_classification |
Classify whether the given English sentence is correctly converted to French sentence | Text Matching | Miscellaneous | English, French | English |
task832_poleval2019_mt_classification |
Classify whether the given Polish sentence is correctly converted to English sentence | Text Matching | Miscellaneous | Polish, English | English |
task833_poem_sentiment_classification |
Classify whether the given poem text is positive or negative | Sentiment Analysis | Literature | English | English |
task834_mathdataset_classification |
Classify the type of a math word problem | Question Understanding | Mathematics | English | English |
task835_mathdataset_answer_generation |
Find the numerical answer for a math word problem | Question Answering | Mathematics | English | English |
task836_viquiquad_question_generation |
Given a passage in the Catalan language, generate contextual questions | Question Generation | Wikipedia | Catalan | Catalan |
task837_viquiquad_answer_generation |
Given a passage and asked a question in the Catalan language, answer that question | Question Answering | Wikipedia | Catalan | Catalan |
task838_cdt_classification |
Given a tweet, determine if it has bullying content. (based on cdt) | Toxic Language Detection | Social Media -> Twitter | Polish | English |
task839_cdt_classification |
Given a tweet and prompt, determine if it has bullying content. (based on cdt) | Toxic Language Detection | Social Media -> Twitter | Polish | English |
task840_para_pdt_en_es_translation |
Translate English questions to Spanish while preserving named entities in the original language. (based on para_pdt) | Translation | Natural Science | Spanish | English |
task841_para_pdt_de_en_translation |
Translate German questions to English while preserving named entities in the original language. (based on para_pdt) | Translation | Natural Science | German | English |
task842_para_pdt_cs_en_translation |
Translate Czech questions to English while preserving named entities in the original language. (based on para_pdt) | Translation | Natural Science | Czech | English |
task843_financial_phrasebank_classification |
Classifying news into positive, neutral, and negative (based on financial_phrasebank) | Sentiment Analysis | News | English | English |
task844_financial_phrasebank_classification |
Classifying if (news, polarity) is valid or not (based on financial_phrasebank) | Sentiment Analysis | News | English | English |
task845_pubmedqa_question_generation |
Generating question from context and answer (based on pubmed_QA) | Question Generation | Medicine | English | English |
task846_pubmedqa_classification |
Classifying if the given answer pertains to the question or not (based on pubmed_QA) | Answer Verification | Medicine | English | English |
task847_pubmedqa_question_generation |
Generating question from context (based on pubmed_QA) | Question Generation | Medicine | English | English |
task848_pubmedqa_classification |
Classifying if the objective is present or not (based on pubmed_QA) | Intent Identification | Medicine | English | English |
task849_pubmedqa_answer_generation |
Generating answer from context and question (based on pubmed_QA) | Question Answering | Medicine | English | English |
task850_synthetic_longest_palindrome |
Given a string find the longest substring that is a palindrome. | Program Execution | Code, Mathematics | English | English |
task851_synthetic_multiply_evens |
Given a list of lists of integers multiply the even numbers in every list | Program Execution | Code, Mathematics | English | English |
task852_synthetic_multiply_odds |
Given a list of lists of integers multiply the odd numbers in every list | Program Execution | Code, Mathematics | English | English |
task853_hippocorpus_long_text_generation |
Generating long text given summaries (based on HIPPOCORPUS) | Story Composition | Story | English | English |
task854_hippocorpus_classification |
Classifying whether a story is imagined, recalled, or retold (based on HIPPOCORPUS) | Text Categorization | Story | English | English |
task855_conv_ai_2_classification |
Classifying whether one conversation participant is a bot or human (based on conv_ai_2) | Speaker Identification | Dialogue | English | English |
task856_conv_ai_2_classification |
Classifying whether a conversation starter is written by a bot or a human (based on conv_ai_2) | Speaker Identification | Dialogue | English | English |
task857_inquisitive_question_generation |
Generating inquisitive questions | Question Generation | News | English | English |
task858_inquisitive_span_detection |
Detecting span of sentence | Question Answering | News | English | English |
task859_prost_question_generation |
Question generation | Question Generation | Commonsense -> Concepts and Relations | English | English |
task860_prost_mcq_generation |
Generating MCQs | Question Generation | Commonsense -> Concepts and Relations | English | English |
task861_prost_mcq_answers_generation |
Generating answers of MCQs | Question Generation | Commonsense -> Concepts and Relations | English | English |
task861_asdiv_addsub_question_answering |
Given a mathematical question , find the most suitable numerical answer | Question Answering | Mathematics | English | English |
task862_asdiv_multidiv_question_answering |
Given a mathematical question , find the most suitable numerical answer | Question Answering | Mathematics | English | English |
task863_asdiv_multiop_question_answering |
Given a mathematical question , find the most suitable numerical answer | Question Answering | Mathematics | English | English |
task864_asdiv_singleop_question_answering |
Given a mathematical question , find the most suitable numerical answer | Question Answering | Mathematics | English | English |
task865_mawps_addsub_question_answering |
Given a mathematical question , find the most suitable numerical answer | Question Answering | Mathematics | English | English |
task866_mawps_multidiv_question_answering |
Given a mathematical question , find the most suitable numerical answer | Question Answering | Mathematics | English | English |
task867_mawps_multiop_question_answering |
Given a mathematical question , find the most suitable numerical answer | Question Answering | Mathematics | English | English |
task868_mawps_singleop_question_answering |
Given a mathematical question , find the most suitable numerical answer | Question Answering | Mathematics | English | English |
task868_cfq_mcd1_explanation_to_sql |
Generating queries (based on CFQ MCD1) | Text to Code | Code -> Language -> SQL | English | English |
task869_cfq_mcd1_sql_to_explanation |
Checking if queries match natural language query description | Text to Code | Code -> Language -> SQL | English | English |
task870_msmarco_answer_generation |
Generating answers based on natural language passage and related query from MS MARCO | Question Answering | Global Facts | English | English |
task871_msmarco_question_generation |
Generating questions based on natural language passage from MS MARCO | Question Generation | Global Facts | English | English |
task872_opus_xhosanavy_translation_eng_xhosa |
Translate a sentence in English to Xhosa | Translation | Miscellaneous | English | Xhosa |
task873_opus_xhosanavy_translation_xhosa_eng |
Translate a sentence in Xhosa to English | Translation | Miscellaneous | Xhosa | English |
task874_opus_xhosanavy_sr |
Recognize primary subjects in sentences | Information Extraction | Miscellaneous | English | English |
task875_emotion_classification |
Classify sentences by emotions | Sentiment Analysis | Narrative | English | English |
task877_kde4_translation |
Localizing English phrases to Hindi language | Translation | Computer Science | English | Hindi |
task878_kde4_translation |
Localizing English phrases to Telugu language | Translation | Computer Science | English | Telugu |
task879_schema_guided_dstc8_classification |
Classifying sentence as question or not | Dialogue Act Recognition | Dialogue | English | English |
task880_schema_guided_dstc8_classification |
Classifying sentence into one of five action categories | Dialogue Act Recognition | Dialogue | English | English |
task881_schema_guided_dstc8_classification |
Identifying which one of five services the sentence is related to | Text Categorization | Dialogue | English | English |
task886_quail_question_generation |
Generating questions based on passages | Question Generation | Narrative, Fiction, News | English | English |
task887_quail_answer_generation |
Generating answer for a given question based on passages | Question Answering | Narrative, Fiction, News | English | English |
task888_reviews_classification |
Classifying whether a review is positive or negative | Sentiment Analysis | Reviews -> Movies | English | English |
task889_goemotions_classification |
Classifying the sentence to an emotion class | Sentiment Analysis | Narrative, Dialogue | English | English |
task890_gcwd_classification |
Classifying writer's stance to Global Warming | Textual Entailment | Economics | English | English |
task891_gap_coreference_resolution |
Finding names for given pronouns | Coreference Resolution | Wikipedia | English | English |
task892_gap_reverse_coreference_resolution |
Finding pronouns for given names | Coreference Resolution | Wikipedia | English | English |
task893_gap_fill_the_blank_coreference_resolution |
Fill the blanks with corresponding pronouns | Coreference Resolution | Wikipedia | English | English |
task896_miam_language_classification |
Classify the language for Dialogue utterances | Language Identification | Dialogue | English, French, German, Italian, Spanish | English |
task897_freebase_qa_topic_question_generation |
Generate question for the given topic | Question Generation | Wikipedia | English | English |
task898_freebase_qa_answer_generation |
Answering questions based on an open ended topic | Question Answering | Wikipedia | English | English |
task899_freebase_qa_topic_generation |
Generate the specific topic for a given question | Question Understanding | Wikipedia | English | English |
task900_freebase_qa_category_classification |
Classify the general category for questions | Question Understanding | Wikipedia | English | English |
task901_freebase_qa_category_question_generation |
Generate trivia type questions based on a broad category | Question Generation | Wikipedia | English | English |
task902_deceptive_opinion_spam_classification |
Identity polarity of hotel reviews | Sentiment Analysis | Reviews | English | English |
task903_deceptive_opinion_spam_classification |
Given hotel reviews and it's polarity, determine whether it's true or false | Sentiment Analysis | Reviews | English | English |
task904_hate_speech_offensive_classification |
Classify tweets into hate speech, offensive or neither | Toxic Language Detection | Social Media -> Twitter | English | English |
task905_hate_speech_offensive_classification |
Given tweet and it's category, determine whether it's true or false | Toxic Language Detection | Social Media -> Twitter | English | English |
task906_dialogre_identify_names |
Text Identification with DialogRE | Speaker Identification | Dialogue | English | English |
task907_dialogre_identify_relationships |
Classifying Relationships with DialogRE | Speaker Relation Classification | Dialogue | English | English |
task908_dialogre_identify_familial_relationships |
Classifying Familial Relationships with DialogRE | Speaker Relation Classification | Dialogue | English | English |
task909_dialogre_prevalent_speakers |
Classifying Prevalent Speakers with DialogRE | Speaker Identification | Dialogue | English | English |
task910_bianet_classification |
Classifying whether two sentences are translations of each other | Text Matching | News | English, Kurdish | English |
task911_bianet_translation |
Generating a translation of an English sentence into Kurdish | Translation | News | English | Kurdish |
task912_bianet_classification |
Classifying a given sentence into English or Kurdish | Language Identification | News | English, Kurdish | English |
task913_bianet_translation |
Generating a translation of an English sentence into Turkish | Translation | News | English | Turkish |
task914_bianet_translation |
Generating a translation of a Kurdish sentence into Turkish | Translation | News | Kurdish | Turkish |
task917_coqa_question_generation |
Given a passage, generate a question | Question Generation | Story | English | English |
task918_coqa_answer_generation |
Given a passage and a question, generate an answer for that question | Question Answering | Story | English | English |
task919_coqa_incorrect_answer_generation |
Given a passage and a question, generate an incorrect answer which is irrelevant for that question and passage | Wrong Candidate Generation | Story | English | English |
task921_code_x_glue_information_retreival |
Given a code, calculate the number of "for loops" in the cpp program | Misc. | Code | English | English |
task922_event2mind_word_generation |
Generating emotion words from Event2Mind based on PersonX | Misc. | Commonsense -> Concepts and Relations | English | English |
task923_event2mind_classifier |
Classifying results based on sentiment values from Event2Mind | Sentiment Analysis | Commonsense -> Concepts and Relations | English | English |
task924_event2mind_word_generation |
Generating emotion words from Event2Mind based on Other Person | Misc. | Commonsense -> Concepts and Relations | English | English |
task925_coached_conv_pref_classifier |
Classifying results to find next speaker from coached_conv_pref | Speaker Identification | Dialogue | English | English |
task926_coached_conv_pref_word_generation |
Generating movie names from PersonX name from coached_conv_pref | Information Extraction | Dialogue | English | English |
task927_yelp_negative_to_positive_style_transfer |
Given a negative review change it to a postive review | Style Transfer | Reviews | English | English |
task928_yelp_positive_to_negative_style_transfer |
Given a postive review change it to a negative review | Style Transfer | Reviews | English | English |
task929_products_reviews_classification |
Classifying generated_reviews_enth whether the review is Good Review or Bad Review | Sentiment Analysis | Reviews | English | English |
task930_dailydialog_classification |
Classifying Data of DailyDialog whether the topic of conversation is Tourism or Not in the dialogue | Text Categorization | Dialogue | English | English |
task931_dailydialog_classification |
Classifying Data of DailyDialog whether happy or sad emotion in the dialogue | Sentiment Analysis | Dialogue | English | English |
task932_dailydialog_classification |
Classifying Data of DailyDialog whether there is question in the dialogue or not | Intent Identification | Dialogue | English | English |
task933_wiki_auto_style_transfer |
Rewrite wikipedia sentences in simple English. | Text Simplification | Wikipedia | English | English |
task934_turk_simplification |
Given a sentence your task is to generate possible numbers of simplified sentences. | Text Simplification | Wikipedia | English | English |
task935_defeasible_nli_atomic_classification |
Given a premise, hypothesis and an update, indentify whether the update strengthens or weakens the hypothesis. | Textual Entailment | Commonsense -> Concepts and Relations | English | English |
task936_defeasible_nli_snli_classification |
Given a premise, hypothesis and an update, indentify whether the update strengthens or weakens the hypothesis. | Textual Entailment | Captions -> Image Captions | English | English |
task937_defeasible_nli_social_classification |
Given a hypothesis and an update, indentify whether the update strengthens or weakens the hypothesis. | Textual Entailment | Commonsense -> Concepts and Relations | English | English |
task938_copa_hi_commonsense_reasoning |
Given a premise and two alternative in hindi, select the alternative that more plausibly has a causal relation with the premise | Cause Effect Classification | Commonsense -> Concepts and Relations | Hindi | Hindi |
task939_copa_hi_commonsense_cause_effect |
Given a pair of sentences in hindi, judge whether the second sentence is the cause or effect of the first on. | Cause Effect Classification | Commonsense -> Concepts and Relations | Hindi | English |
task940_copa_gu_commonsense_reasoning |
Given a premise and two alternative in gujarati, select the alternative that more plausibly has a causal relation with the premise | Cause Effect Classification | Commonsense -> Concepts and Relations | Gujarati | Gujarati |
task941_copa_gu_commonsense_cause_effect |
Given a pair of sentences in gujarati, judge whether the second sentence is the cause or effect of the first on. | Cause Effect Classification | Commonsense -> Concepts and Relations | Gujarati | English |
task942_copa_mr_commonsense_reasoning |
Given a premise and two alternative in marathi, select the alternative that more plausibly has a causal relation with the premise | Cause Effect Classification | Commonsense -> Concepts and Relations | Marathi | Marathi |
task943_copa_mr_commonsense_cause_effect |
Given a pair of sentences in marathi, judge whether the second sentence is the cause or effect of the first on. | Cause Effect Classification | Commonsense -> Concepts and Relations | Marathi | English |
task944_wiki_cloze_as_multiple_choice_question_answering |
Given a cloze question in assamese, identify the missing word | Fill in The Blank | Web | Assamese | Assamese |
task945_wiki_cloze_bn_multiple_choice_question_answering |
Given a cloze question in bengali, identify the missing word | Fill in The Blank | Web | Bengali | Bengali |
task946_wiki_cloze_gu_multiple_choice_question_answering |
Given a cloze question in gujarati, identify the missing word | Fill in The Blank | Web | Gujarati | Gujarati |
task947_wiki_cloze_hi_multiple_choice_question_answering |
Given a cloze question in hindi, identify the missing word | Fill in The Blank | Web | Hindi | Hindi |
task948_wiki_cloze_kn_multiple_choice_question_answering |
Given a cloze question in kannada, identify the missing word | Fill in The Blank | Web | Kannada | Kannada |
task949_wiki_cloze_ml_multiple_choice_question_answering |
Given a cloze question in malayalam, identify the missing word | Fill in The Blank | Web | Malayalam | Malayalam |
task950_wiki_cloze_mr_multiple_choice_question_answering |
Given a cloze question in marathi, identify the missing word | Fill in The Blank | Web | Marathi | Marathi |
task951_wiki_cloze_or_multiple_choice_question_answering |
Given a cloze question in odia, identify the missing word | Fill in The Blank | Web | Oriya | Oriya |
task952_wiki_cloze_pa_multiple_choice_question_answering |
Given a cloze question in punjabi, identify the missing word | Fill in The Blank | Web | Panjabi | Panjabi |
task953_wiki_cloze_ta_multiple_choice_question_answering |
Given a cloze question in tamil, identify the missing word | Fill in The Blank | Web | Tamil | Tamil |
task954_wiki_cloze_te_multiple_choice_question_answering |
Given a cloze question in telugu, identify the missing word | Fill in The Blank | Web | Telugu | Telugu |
task955_wiki_auto_style_transfer |
Elaborate wikipedia sentences. | Sentence Expansion | Wikipedia | English | English |
task956_leetcode_420_strong_password_check |
Check if the given password is strong | Text to Code | Mathematics | English | English |
task957_e2e_nlg_text_generation_generate |
Generate a restaurant description from a data table. | Data to Text | Public Places -> Restaurants | English | English |
task958_e2e_nlg_text_generation_parse |
Parse a restaurant description into a data table. | Information Extraction | Public Places -> Restaurants | English | English |
task959_e2e_nlg_text_generation_identify |
Identify the named entity that is the subject of the excerpt. | Named Entity Recognition | Public Places -> Restaurants | English | English |
task960_ancora-ca-ner_named_entity_recognition |
Named Entity Recognition for each token in BSC-TeMU/ancora-ca-ner catalan sentences | Named Entity Recognition | News | Catalan | Catalan |
task961_ancora-ca-ner_text_auto_completion |
Text Auto Completion of partial Catalan sentences | Text Completion | News | Catalan | Catalan |
task962_ancora-ca-ner_missing_word_prediction |
Generating a missing word on Catalan Sentences | Fill in The Blank | News | Catalan | Catalan |
task963_librispeech_asr_next_word_prediction |
Predicting next word on librispeech data | Text Completion | Books | English | English |
task964_librispeech_asr_text_auto_completion |
Text Auto Completion of partial English sentences | Text Completion | Books | English | English |
task965_librispeech_asr_missing_word_prediction |
Generating a missing word on English Sentences | Fill in The Blank | Books | English | English |
task966_ruletaker_fact_checking_based_on_given_context |
Fact checking based on given context | Fact Verification | Commonsense -> Concepts and Relations | English | English |
task967_ruletaker_incorrect_fact_generation_based_on_given_paragraph |
Generate incorrect fact based on given paragraph | Wrong Candidate Generation | Commonsense -> Concepts and Relations | English | English |
task968_xcopa_commonsense_reasoning_et |
Given a premise and two alternative in Estonian, select the alternative that more plausibly has a causal relation with the premise | Cause Effect Classification | Personal Narratives | Estonian | English |
task969_xcopa_commonsense_cause_effect_et |
Given a pair of sentences in Estonian, judge whether the second sentence is the cause or effect of the first on. | Cause Effect Classification | Personal Narratives | Estonian | English |
task970_sherliic_causal_relationship |
Determine if A and B share a casual relationship | Textual Entailment | Formal logic | English | English |
task974_prachathai67k_sentiment_classification |
Classify the sentiment of a given article on the given genre | Sentiment Analysis | News | English, Thai | English |
task975_prachathai67k_same_genre_classification |
Determine if the two articles given share the same sentiment fot the given genre | Sentiment Analysis | News | English, Thai | English |
task976_pib_indian_language_identification |
Identify the language of the given statement from the 11 languages listed | Language Identification | Sociology, News | English, Gujarati, Hindi, Malayalam, Panjabi, Marathi, Oriya, Tamil, Bengali, Telugu, Urdu | English |
task977_pib_translation_oriya_urdu |
Translate from oriya to urdu | Translation | Sociology, News | Oriya | Urdu |
task978_pib_translation_urdu_oriya |
Translate from urdu to oriya | Translation | Sociology, News | Urdu | Oriya |
task979_pib_translation_malayalam_oriya |
Translate from malayalam to oriya | Translation | Sociology, News | Malayalam | Oriya |
task980_pib_translation_oriya_malayalam |
Translate from oriya to malayalam | Translation | Sociology, News | Oriya | Malayalam |
task981_pib_translation_bengali_tamil |
Translate from bengali to tamil | Translation | Sociology, News | Bengali | Tamil |
task982_pib_translation_tamil_bengali |
Translate from tamil to bengali | Translation | Sociology, News | Tamil | Bengali |
task983_pib_translation_gujarati_marathi |
Translate from gujarati to marathi | Translation | Sociology, News | Gujarati | Marathi |
task984_pib_translation_marathi_gujarati |
Translate from marathi to gujarati | Translation | Sociology, News | Marathi | Gujarati |
task985_pib_translation_hindi_oriya |
Translate from hindi to oriya | Translation | Sociology, News | Hindi | Oriya |
task986_pib_translation_oriya_hindi |
Translate from oriya to hindi | Translation | Sociology, News | Oriya | Hindi |
task987_pib_translation_english_oriya |
Translate from english to oriya | Translation | Sociology, News | English | Oriya |
task988_pib_translation_oriya_english |
Translate from oriya to english | Translation | Sociology, News | Oriya | English |
task989_pib_translation_marathi_urdu |
Translate from marathi to urdu | Translation | Sociology, News | Marathi | Urdu |
task990_pib_translation_urdu_marathi |
Translate from urdu to marathi | Translation | Sociology, News | Urdu | Marathi |
task991_pib_translation_english_tamil |
Translate from english to tamil | Translation | Sociology, News | English | Tamil |
task992_pib_translation_tamil_english |
Translate from tamil to english | Translation | Sociology, News | Tamil | English |
task993_pib_translation_hindi_tamil |
Translate from hindi to tamil | Translation | Sociology, News | Hindi | Tamil |
task994_pib_translation_tamil_hindi |
Translate from tamil to hindi | Translation | Sociology, News | Tamil | Hindi |
task995_pib_translation_bengali_english |
Translate from bengali to english | Translation | Sociology, News | Bengali | English |
task996_pib_translation_english_bengali |
Translate from english to bengali | Translation | Sociology, News | English | Bengali |
task997_pib_translation_bengali_oriya |
Translate from bengali to oriya | Translation | Sociology, News | Bengali | Oriya |
task998_pib_translation_oriya_bengali |
Translate from oriya to bengali | Translation | Sociology, News | Oriya | Bengali |
task999_pib_translation_malayalam_tamil |
Translate from malayalam to tamil | Translation | Sociology, News | Malayalam | Tamil |
task1000_pib_translation_tamil_malayalam |
Translate from tamil to malayalam | Translation | Sociology, News | Tamil | Malayalam |
task1001_pib_translation_gujarati_urdu |
Translate from gujarati to urdu | Translation | Sociology, News | Gujarati | Urdu |
task1002_pib_translation_urdu_gujarati |
Translate from urdu to gujarati | Translation | Sociology, News | Urdu | Gujarati |
task1003_pib_translation_bengali_malayalam |
Translate from bengali to malayalam | Translation | Sociology, News | Bengali | Malayalam |
task1004_pib_translation_malayalam_bengali |
Translate from malayalam to bengali | Translation | Sociology, News | Malayalam | Bengali |
task1005_pib_translation_malayalam_punjabi |
Translate from malayalam to punjabi | Translation | Sociology, News | Malayalam | Panjabi |
task1006_pib_translation_punjabi_malayalam |
Translate from punjabi to malayalam | Translation | Sociology, News | Panjabi | Malayalam |
task1007_pib_translation_english_punjabi |
Translate from english to punjabi | Translation | Sociology, News | English | Panjabi |
task1008_pib_translation_punjabi_english |
Translate from punjabi to english | Translation | Sociology, News | Panjabi | English |
task1009_pib_translation_bengali_hindi |
Translate from bengali to hindi | Translation | Sociology, News | Bengali | Hindi |
task1010_pib_translation_hindi_bengali |
Translate from hindi to bengali | Translation | Sociology, News | Hindi | Bengali |
task1011_pib_translation_hindi_punjabi |
Translate from hindi to punjabi | Translation | Sociology, News | Hindi | Panjabi |
task1012_pib_translation_punjabi_hindi |
Translate from punjabi to hindi | Translation | Sociology, News | Panjabi | Hindi |
task1013_pib_translation_gujarati_telugu |
Translate from gujarati to telugu | Translation | Sociology, News | Gujarati | Telugu |
task1014_pib_translation_telugu_gujarati |
Translate from telugu to gujarati | Translation | Sociology, News | Telugu | Gujarati |
task1015_pib_translation_punjabi_tamil |
Translate from punjabi to tamil | Translation | Sociology, News | Panjabi | Tamil |
task1016_pib_translation_tamil_punjabi |
Translate from tamil to punjabi | Translation | Sociology, News | Tamil | Panjabi |
task1017_pib_translation_hindi_malayalam |
Translate from hindi to malayalam | Translation | Sociology, News | Hindi | Malayalam |
task1018_pib_translation_malayalam_hindi |
Translate from malayalam to hindi | Translation | Sociology, News | Malayalam | Hindi |
task1019_pib_translation_oriya_telugu |
Translate from oriya to telugu | Translation | Sociology, News | Oriya | Telugu |
task1020_pib_translation_telugu_oriya |
Translate from telugu to oriya | Translation | Sociology, News | Telugu | Oriya |
task1021_pib_translation_english_malayalam |
Translate from english to malayalam | Translation | Sociology, News | English | Malayalam |
task1022_pib_translation_malayalam_english |
Translate from malayalam to english | Translation | Sociology, News | Malayalam | English |
task1023_pib_translation_english_hindi |
Translate from english to hindi | Translation | Sociology, News | English | Hindi |
task1024_pib_translation_hindi_english |
Translate from hindi to english | Translation | Sociology, News | Hindi | English |
task1025_pib_translation_bengali_punjabi |
Translate from bengali to punjabi | Translation | Sociology, News | Bengali | Panjabi |
task1026_pib_translation_punjabi_bengali |
Translate from punjabi to bengali | Translation | Sociology, News | Panjabi | Bengali |
task1027_pib_translation_marathi_telugu |
Translate from marathi to telugu | Translation | Sociology, News | Marathi | Telugu |
task1028_pib_translation_telugu_marathi |
Translate from telugu to marathi | Translation | Sociology, News | Telugu | Marathi |
task1029_pib_translation_marathi_punjabi |
Translate from marathi to punjabi | Translation | Sociology, News | Marathi | Panjabi |
task1030_pib_translation_punjabi_marathi |
Translate from punjabi to marathi | Translation | Sociology, News | Panjabi | Marathi |
task1031_pib_translation_bengali_telugu |
Translate from bengali to telugu | Translation | Sociology, News | Bengali | Telugu |
task1032_pib_translation_telugu_bengali |
Translate from telugu to bengali | Translation | Sociology, News | Telugu | Bengali |
task1033_pib_translation_gujarati_hindi |
Translate from gujarati to hindi | Translation | Sociology, News | Gujarati | Hindi |
task1034_pib_translation_hindi_gujarati |
Translate from hindi to gujarati | Translation | Sociology, News | Hindi | Gujarati |
task1035_pib_translation_tamil_urdu |
Translate from tamil to urdu | Translation | Sociology, News | Tamil | Urdu |
task1036_pib_translation_urdu_tamil |
Translate from urdu to tamil | Translation | Sociology, News | Urdu | Tamil |
task1037_pib_translation_telugu_urdu |
Translate from telugu to urdu | Translation | Sociology, News | Telugu | Urdu |
task1038_pib_translation_urdu_telugu |
Translate from urdu to telugu | Translation | Sociology, News | Urdu | Telugu |
task1039_pib_translation_oriya_punjabi |
Translate from oriya to punjabi | Translation | Sociology, News | Oriya | Panjabi |
task1040_pib_translation_punjabi_oriya |
Translate from punjabi to oriya | Translation | Sociology, News | Panjabi | Oriya |
task1041_pib_translation_gujarati_malayalam |
Translate from gujarati to malayalam | Translation | Sociology, News | Gujarati | Malayalam |
task1042_pib_translation_malayalam_gujarati |
Translate from malayalam to gujarati | Translation | Sociology, News | Malayalam | Gujarati |
task1043_pib_translation_gujarati_punjabi |
Translate from gujarati to punjabi | Translation | Sociology, News | Gujarati | Panjabi |
task1044_pib_translation_punjabi_gujarati |
Translate from punjabi to gujarati | Translation | Sociology, News | Panjabi | Gujarati |
task1045_pib_translation_hindi_telugu |
Translate from hindi to telugu | Translation | Sociology, News | Hindi | Telugu |
task1046_pib_translation_telugu_hindi |
Translate from telugu to hindi | Translation | Sociology, News | Telugu | Hindi |
task1047_pib_translation_english_telugu |
Translate from english to telugu | Translation | Sociology, News | English | Telugu |
task1048_pib_translation_telugu_english |
Translate from telugu to english | Translation | Sociology, News | Telugu | English |
task1049_pib_translation_malayalam_telugu |
Translate from malayalam to telugu | Translation | Sociology, News | Malayalam | Telugu |
task1050_pib_translation_telugu_malayalam |
Translate from telugu to malayalam | Translation | Sociology, News | Telugu | Malayalam |
task1051_pib_translation_punjabi_urdu |
Translate from punjabi to urdu | Translation | Sociology, News | Panjabi | Urdu |
task1052_pib_translation_urdu_punjabi |
Translate from urdu to punjabi | Translation | Sociology, News | Urdu | Panjabi |
task1053_pib_translation_hindi_urdu |
Translate from hindi to urdu | Translation | Sociology, News | Hindi | Urdu |
task1054_pib_translation_urdu_hindi |
Translate from urdu to hindi | Translation | Sociology, News | Urdu | Hindi |
task1055_pib_translation_marathi_oriya |
Translate from marathi to oriya | Translation | Sociology, News | Marathi | Oriya |
task1056_pib_translation_oriya_marathi |
Translate from oriya to marathi | Translation | Sociology, News | Oriya | Marathi |
task1057_pib_translation_english_urdu |
Translate from english to urdu | Translation | Sociology, News | English | Urdu |
task1058_pib_translation_urdu_english |
Translate from urdu to english | Translation | Sociology, News | Urdu | English |
task1059_pib_translation_malayalam_urdu |
Translate from malayalam to urdu | Translation | Sociology, News | Malayalam | Urdu |
task1060_pib_translation_urdu_malayalam |
Translate from urdu to malayalam | Translation | Sociology, News | Urdu | Malayalam |
task1061_pib_translation_bengali_marathi |
Translate from bengali to marathi | Translation | Sociology, News | Bengali | Marathi |
task1062_pib_translation_marathi_bengali |
Translate from marathi to bengali | Translation | Sociology, News | Marathi | Bengali |
task1063_pib_translation_gujarati_tamil |
Translate from gujarati to tamil | Translation | Sociology, News | Gujarati | Tamil |
task1064_pib_translation_tamil_gujarati |
Translate from tamil to gujarati | Translation | Sociology, News | Tamil | Gujarati |
task1065_pib_translation_punjabi_telugu |
Translate from punjabi to telugu | Translation | Sociology, News | Panjabi | Telugu |
task1066_pib_translation_telugu_punjabi |
Translate from telugu to punjabi | Translation | Sociology, News | Telugu | Panjabi |
task1067_pib_translation_bengali_gujarati |
Translate from bengali to gujarati | Translation | Sociology, News | Bengali | Gujarati |
task1068_pib_translation_gujarati_bengali |
Translate from gujarati to bengali | Translation | Sociology, News | Gujarati | Bengali |
task1069_pib_translation_bengali_urdu |
Translate from bengali to urdu | Translation | Sociology, News | Bengali | Urdu |
task1070_pib_translation_urdu_bengali |
Translate from urdu to bengali | Translation | Sociology, News | Urdu | Bengali |
task1071_pib_translation_malayalam_marathi |
Translate from malayalam to marathi | Translation | Sociology, News | Malayalam | Marathi |
task1072_pib_translation_marathi_malayalam |
Translate from marathi to malayalam | Translation | Sociology, News | Marathi | Malayalam |
task1073_pib_translation_oriya_tamil |
Translate from oriya to tamil | Translation | Sociology, News | Oriya | Tamil |
task1074_pib_translation_tamil_oriya |
Translate from tamil to oriya | Translation | Sociology, News | Tamil | Oriya |
task1075_pib_translation_tamil_telugu |
Translate from tamil to telugu | Translation | Sociology, News | Tamil | Telugu |
task1076_pib_translation_telugu_tamil |
Translate from telugu to tamil | Translation | Sociology, News | Telugu | Tamil |
task1077_pib_translation_gujarati_oriya |
Translate from gujarati to oriya | Translation | Sociology, News | Gujarati | Oriya |
task1078_pib_translation_oriya_gujarati |
Translate from oriya to gujarati | Translation | Sociology, News | Oriya | Gujarati |
task1079_pib_translation_english_gujarati |
Translate from english to gujarati | Translation | Sociology, News | English | Gujarati |
task1080_pib_translation_gujarati_english |
Translate from gujarati to english | Translation | Sociology, News | Gujarati | English |
task1081_pib_translation_hindi_marathi |
Translate from hindi to marathi | Translation | Sociology, News | Hindi | Marathi |
task1082_pib_translation_marathi_hindi |
Translate from marathi to hindi | Translation | Sociology, News | Marathi | Hindi |
task1083_pib_translation_marathi_tamil |
Translate from marathi to tamil | Translation | Sociology, News | Marathi | Tamil |
task1084_pib_translation_tamil_marathi |
Translate from tamil to marathi | Translation | Sociology, News | Tamil | Marathi |
task1085_pib_translation_english_marathi |
Translate from english to marathi | Translation | Sociology, News | English | Marathi |
task1086_pib_translation_marathi_english |
Translate from marathi to english | Translation | Sociology, News | Marathi | English |
task1087_two_number_sum |
Given a list of integers and a target sum, return a pair of integers that sum to the target | Program Execution | Mathematics | English | English |
task1088_array_of_products |
Given an integer array in the input, return an array such that its element at each location is equal to the product of elements at every other location in the input array" | Program Execution | Mathematics | English | English |
task1089_check_monotonic_array |
Check if the given array is monotonic or not | Program Execution | Mathematics | English | English |
task1090_ted_translation_en_gl |
Translate a sentence in English to Galician. | Translation | TED Talks, Captions -> Video Captions | English | Galician |
task1091_ted_translation_en_it |
Translate a sentence in English to Italian. | Translation | TED Talks, Captions -> Video Captions | English | Italian |
task1092_ted_translation_en_pl |
Translate a sentence in English to Polish. | Translation | TED Talks, Captions -> Video Captions | English | Polish |
task1093_ted_translation_en_fa |
Translate a sentence in English to Farsi. | Translation | TED Talks, Captions -> Video Captions | English | Persian |
task1094_ted_translation_en_pt |
Translate a sentence in English to Portugese. | Translation | TED Talks, Captions -> Video Captions | English | Portuguese |
task1095_ted_translation_ja_gl |
Translate a sentence in Japanese to Galician. | Translation | TED Talks, Captions -> Video Captions | Japanese | Galician |
task1096_ted_translation_ja_it |
Translate a sentence in Japanese to Italian. | Translation | TED Talks, Captions -> Video Captions | Japanese | Italian |
task1097_ted_translation_ja_pl |
Translate a sentence in Japanese to Polish. | Translation | TED Talks, Captions -> Video Captions | Japanese | Polish |
task1098_ted_translation_ja_fa |
Translate a sentence in Japanese to Farsi. | Translation | TED Talks, Captions -> Video Captions | Japanese | Persian |
task1099_ted_translation_ja_pt |
Translate a sentence in Japanese to Portugese. | Translation | TED Talks, Captions -> Video Captions | Japanese | Portuguese |
task1100_ted_translation_es_gl |
Translate a sentence in Spanish to Galician. | Translation | TED Talks, Captions -> Video Captions | Spanish | Galician |
task1101_ted_translation_es_it |
Translate a sentence in Spanish to Italian. | Translation | TED Talks, Captions -> Video Captions | Spanish | Italian |
task1102_ted_translation_es_pl |
Translate a sentence in Spanish to Polish. | Translation | TED Talks, Captions -> Video Captions | Spanish | Polish |
task1103_ted_translation_es_fa |
Translate a sentence in Spanish to Farsi. | Translation | TED Talks, Captions -> Video Captions | Spanish | Persian |
task1104_ted_translation_es_pt |
Translate a sentence in Spanish to Portugese. | Translation | TED Talks, Captions -> Video Captions | Spanish | Portuguese |
task1105_ted_translation_ar_gl |
Translate a sentence in Arabic to Galician. | Translation | TED Talks, Captions -> Video Captions | Arabic | Galician |
task1106_ted_translation_ar_it |
Translate a sentence in Arabic to Italian. | Translation | TED Talks, Captions -> Video Captions | Arabic | Italian |
task1107_ted_translation_ar_pl |
Translate a sentence in Arabic to Polish. | Translation | TED Talks, Captions -> Video Captions | Arabic | Polish |
task1108_ted_translation_ar_fa |
Translate a sentence in Arabic to Farsi. | Translation | TED Talks, Captions -> Video Captions | Arabic | Persian |
task1109_ted_translation_ar_pt |
Translate a sentence in Arabic to Portugese. | Translation | TED Talks, Captions -> Video Captions | Arabic | Portuguese |
task1110_ted_translation_he_gl |
Translate a sentence in Hebrew to Galician. | Translation | TED Talks, Captions -> Video Captions | Hebrew | Galician |
task1111_ted_translation_he_it |
Translate a sentence in Hebrew to Italian. | Translation | TED Talks, Captions -> Video Captions | Hebrew | Italian |
task1112_ted_translation_he_pl |
Translate a sentence in Hebrew to Polish. | Translation | TED Talks, Captions -> Video Captions | Hebrew | Polish |
task1113_ted_translation_he_fa |
Translate a sentence in Hebrew to Farsi. | Translation | TED Talks, Captions -> Video Captions | Hebrew | Persian |
task1114_ted_translation_he_pt |
Translate a sentence in Hebrew to Portugese. | Translation | TED Talks, Captions -> Video Captions | Hebrew | Portuguese |
task1115_alt_ja_id_translation |
Given a Japanese language sentence translate it into Bahasa Indonesia language. | Translation | News | Japanese | Indonesian |
task1116_alt_id_ja_translation |
Given a Bahasa Indonesia language sentence translate it into Japanese language. | Translation | News | Indonesian | Japanese |
task1117_alt_ja_id_answer_generation |
Generate answer yes or no for Japanese and Bahasa Indonesia translation pair. | Text Matching | News | Japanese, Indonesian | English |
task1118_alt_ja_fil_translation |
Given a Japanese language sentence translate it into Filipino language. | Translation | News | Japanese | Filipino |
task1119_alt_fil_ja_translation |
Given a Filipino language sentence translate it into Japanese language. | Translation | News | Filipino | Japanese |
task1120_alt_ja_fil_answer_generation |
Generate answer yes or no for Japanese and Filipino translation pair. | Text Matching | News | Japanese, Filipino | Japanese |
task1121_alt_ja_khm_translation |
Given a Japanese language sentence translate it into Khmer language. | Translation | News | Japanese | Central Khmer |
task1122_alt_khm_ja_translation |
Given a Khmer language sentence translate it into Japanese language. | Translation | News | Central Khmer | Japanese |
task1123_alt_ja_khm_answer_generation |
Generate answer yes or no for Japanese and Khmer translation pair. | Text Matching | News | Central Khmer, Japanese | English |
task1124_alt_ja_lo_translation |
Given a Japanese language sentence translate it into Lao language. | Translation | News | Japanese | Lao |
task1125_alt_lo_ja_translation |
Given a Lao language sentence translate it into Japanese language. | Translation | News | Lao | Japanese |
task1126_alt_ja_lo_answer_generation |
Generate answer yes or no for Japanese and Lao translation pair. | Text Matching | News | Japanese, Lao | English |
task1127_alt_ja_th_translation |
Given a Japanese language sentence translate it into Thai language. | Translation | News | Japanese | Thai |
task1128_alt_th_ja_translation |
Given a Thai language sentence translate it into Japanese language. | Translation | News | Thai | Japanese |
task1129_alt_ja_th_answer_generation |
Generate answer yes or no for Japanese and Thai translation pair. | Text Matching | News | Japanese, Thai | English |
task1130_xcsr_vi_commonsense_mc_classification |
Answering multiple choice commonsense question in Vietnamese language. | Question Answering | Commonsense | Vietnamese | English |
task1131_xcsr_es_commonsense_mc_classification |
Answering multiple choice commonsense question in Spanish language. | Question Answering | Commonsense | Spanish | English |
task1132_xcsr_ur_commonsense_mc_classification |
Answering multiple choice commonsense question in Urdu language. | Question Answering | Commonsense | Urdu | English |
task1133_xcsr_nl_commonsense_mc_classification |
Answering multiple choice commonsense question in Dutch language. | Question Answering | Commonsense | Dutch | English |
task1134_xcsr_hi_commonsense_mc_classification |
Answering multiple choice commonsense question in Hindi language. | Question Answering | Commonsense | Hindi | English |
task1135_xcsr_en_commonsense_mc_classification |
Answering multiple choice commonsense question in English language. | Question Answering | Commonsense | English | English |
task1136_xcsr_fr_commonsense_mc_classification |
Answering multiple choice commonsense question in French language. | Question Answering | Commonsense | French | English |
task1137_xcsr_pt_commonsense_mc_classification |
Answering multiple choice commonsense question in Portuguese language. | Question Answering | Commonsense | Portuguese | English |
task1138_xcsr_de_commonsense_mc_classification |
Answering multiple choice commonsense question in German language. | Question Answering | Commonsense | German | English |
task1139_xcsr_ru_commonsense_mc_classification |
Answering multiple choice commonsense question in Russian language. | Question Answering | Commonsense | Russian | English |
task1140_xcsr_pl_commonsense_mc_classification |
Answering multiple choice commonsense question in Polish language. | Question Answering | Commonsense | Polish | English |
task1141_xcsr_zh_commonsense_mc_classification |
Answering multiple choice commonsense question in Chinese language. | Question Answering | Commonsense | Chinese | English |
task1142_xcsr_ar_commonsense_mc_classification |
Answering multiple choice commonsense question in Arabic language. | Question Answering | Commonsense | Arabic | English |
task1143_xcsr_it_commonsense_mc_classification |
Answering multiple choice commonsense question in Italian language. | Question Answering | Commonsense | Italian | English |
task1144_xcsr_sw_commonsense_mc_classification |
Answering multiple choice commonsense question in Swahili language. | Question Answering | Commonsense | Swahili | English |
task1145_xcsr_jap_commonsense_mc_classification |
Answering multiple choice commonsense question in Japanese language. | Question Answering | Commonsense | Japanese | English |
task1146_country_capital |
Given a country, return it's capital city | Misc. | Countries | English | English |
task1147_country_currency |
Given a country, return it's currency | Misc. | Countries | English | English |
task1148_maximum_ascii_value |
Given a string, return the character with maximum ascii value | Program Execution | Computer Science | English | English |
task1149_item_check_edible |
Given an item, check if it is edible or not | Misc. | Commonsense, Food | English | English |
task1150_delete_max_min |
Given a list of integers, delete the minimum and maximum element from the list | Program Execution | Mathematics | English | English |
task1151_swap_max_min |
Given a list of unique integers, swap the minimum and maximum element in the list | Program Execution | Mathematics | English | English |
task1152_bard_analogical_reasoning_causation |
Given an analogy that relates actions with their consequences, give the appropriate consequence of the given action | Word Analogy | Commonsense | English | English |
task1153_bard_analogical_reasoning_affordance |
Given an analogy that signifies affordances give the appropriate affordance of the given action | Word Analogy | Commonsense | English | English |
task1154_bard_analogical_reasoning_travel |
Given an analogy that relates places/locations to the associated travel mode, give the appropriate travel mode for the given place | Word Analogy | Commonsense, Public Places | English | English |
task1155_bard_analogical_reasoning_trash_or_treasure |
Given an analogy that relates items to whether they are trash or treasure, is the given item trash or treasure? |
Word Analogy | Commonsense | English | English |
task1156_bard_analogical_reasoning_tools |
Given an analogy that relates actions to the tools used to perform the action, give the appropriate tool for the given action | Word Analogy | Commonsense | English | English |
task1157_bard_analogical_reasoning_rooms_for_containers |
Given an analogy that relates objects to the associated rooms, give the appropriate room for the given object | Word Analogy | Commonsense | English | English |
task1158_bard_analogical_reasoning_manipulating_items |
Given an analogy that on manipulating items in a kitchen, give with the appropriate word | Word Analogy | Commonsense | English | English |
task1159_bard_analogical_reasoning_containers |
Given an analogy that relates items to the associated containers, give the appropriate container for the given item | Word Analogy | Commonsense | English | English |
task1161_coda19_title_generation |
Given a paragraph from a research paper, your task is to generate the title of the paper | Title Generation | Scientific Research Papers | English | English |
task1162_coda19_title_classification |
Given a paragraph from the research paper and the title, your task is to classify whether title belong to paper. | Text Matching | Scientific Research Papers | English | English |
task1163_coda19_section_classification |
Given a sentence from a research paper, your task is to classify among the section the sentence belongs. | Section Classification | Scientific Research Papers | English | English |
task1164_coda19_section_correction_classification |
Given a sentence from a research paper and the section, your task is to classify whether the sentence belongs to that sentence. | Section Classification | Scientific Research Papers | English | English |
task1167_penn_treebank_coarse_pos_tagging |
Given a sentence, a word in that sentence and the position of that word in the sentence, find the parts-of-speech tag of the word | Pos Tagging | News, Story | English | English |
task1168_brown_coarse_pos_tagging |
Given a sentence, a word in that sentence and the position of that word in the sentence, find the parts-of-speech tag of the word | Pos Tagging | Miscellaneous | English | English |
task1168_xcopa_commonsense_reasoning_ht |
Given a premise and two alternative in Haitian, select the alternative that more plausibly has a causal relation with the premise | Cause Effect Classification | Commonsense, Narrative | Haitian | English |
task1169_xcopa_commonsense_cause_effect_ht |
Given a pair of sentences in Haitian, judge whether the second sentence is the cause or effect of the first on. | Cause Effect Classification | Commonsense, Narrative | Haitian | English |
task1170_xcopa_commonsense_reasoning_id |
Given a premise and two alternative in Indonesian, select the alternative that more plausibly has a causal relation with the premise | Cause Effect Classification | Commonsense, Narrative | Indonesian | English |
task1171_xcopa_commonsense_cause_effect_id |
Given a pair of sentences in Indonesian, judge whether the second sentence is the cause or effect of the first on. | Cause Effect Classification | Commonsense, Narrative | Indonesian | English |
task1172_xcopa_commonsense_reasoning_it |
Given a premise and two alternative in Italian, select the alternative that more plausibly has a causal relation with the premise | Cause Effect Classification | Commonsense, Narrative | Italian | English |
task1173_xcopa_commonsense_cause_effect_it |
Given a pair of sentences in Italian, judge whether the second sentence is the cause or effect of the first on. | Cause Effect Classification | Commonsense, Narrative | Italian | English |
task1174_xcopa_commonsense_reasoning_sw |
Given a premise and two alternative in Swahili, select the alternative that more plausibly has a causal relation with the premise | Cause Effect Classification | Commonsense, Narrative | Swahili | English |
task1175_xcopa_commonsense_cause_effect_sw |
Given a pair of sentences in Swahili, judge whether the second sentence is the cause or effect of the first on. | Cause Effect Classification | Commonsense, Narrative | Swahili | English |
task1176_xcopa_commonsense_reasoning_ta |
Given a premise and two alternative in Tamil, select the alternative that more plausibly has a causal relation with the premise | Cause Effect Classification | Commonsense, Narrative | Tamil | English |
task1177_xcopa_commonsense_cause_effect_ta |
Given a pair of sentences in Tamil, judge whether the second sentence is the cause or effect of the first on. | Cause Effect Classification | Commonsense, Narrative | Tamil | English |
task1178_xcopa_commonsense_reasoning_th |
Given a premise and two alternative in Thai, select the alternative that more plausibly has a causal relation with the premise | Cause Effect Classification | Commonsense, Narrative | Thai | English |
task1179_xcopa_commonsense_cause_effect_th |
Given a pair of sentences in Thai, judge whether the second sentence is the cause or effect of the first on. | Cause Effect Classification | Commonsense, Narrative | Thai | English |
task1180_xcopa_commonsense_reasoning_tr |
Given a premise and two alternative in Turkish, select the alternative that more plausibly has a causal relation with the premise | Cause Effect Classification | Commonsense, Narrative | Turkish | English |
task1181_xcopa_commonsense_cause_effect_tr |
Given a pair of sentences in Turkish, judge whether the second sentence is the cause or effect of the first on. | Cause Effect Classification | Commonsense, Narrative | Turkish | English |
task1182_xcopa_commonsense_reasoning_vi |
Given a premise and two alternative in Vietnamese, select the alternative that more plausibly has a causal relation with the premise | Cause Effect Classification | Commonsense, Narrative | Vietnamese | English |
task1183_xcopa_commonsense_cause_effect_vi |
Given a pair of sentences in Vietnamese, judge whether the second sentence is the cause or effect of the first on. | Cause Effect Classification | Commonsense, Narrative | Vietnamese | English |
task1184_xcopa_commonsense_reasoning_zh |
Given a premise and two alternative in Chinese, select the alternative that more plausibly has a causal relation with the premise | Cause Effect Classification | Commonsense, Narrative | Chinese | English |
task1185_xcopa_commonsense_cause_effect_zh |
Given a pair of sentences in Chinese, judge whether the second sentence is the cause or effect of the first on. | Cause Effect Classification | Commonsense, Narrative | Chinese | English |
task1186_nne_hrngo_classification |
Evaluate naturalness of system generated reference. | Text Quality Evaluation | Dialogue, Public Places -> Restaurants | English | English |
task1187_politifact_classification |
Given a statement and subject of discussion, your task is to classify whether it's a correct subject or not. | Text Categorization | Government and Politics, News | English | English |
task1188_count_max_freq_char |
Given a string with duplicate characters, find the character which is ocurring with the maximum frequency | Program Execution | Mathematics | English | English |
task1189_check_char_in_string |
Given a string S and a character c, check if c is present in S or not | Program Execution | Mathematics | English | English |
task1190_add_integer_to_list |
Given a list of integers and an integer k, add k to every element in the list | Program Execution | Mathematics | English | English |
task1191_food_veg_nonveg |
Given the name of an indian dish, classify it as non vegetarian or a vegetarian dish | Misc. | Food | English | English |
task1192_food_flavor_profile |
Given the name of an indian dish, classify it's flavor as spicy or sweet | Misc. | Food | English | English |
task1193_food_course_classification |
Given the name of an indian dish, classify it's course as main course, dessert or snack | Misc. | Food | English | English |
task1194_kth_largest_element |
Given a list of integers and an integer k, find the kth largest element in the list | Program Execution | Mathematics | English | English |
task1195_disflqa_disfluent_to_fluent_conversion |
Given a disfluent sentence, modify it to make it a fluent sentence | Question Rewriting | Wikipedia | English | English |
task1196_atomic_classification_oeffect |
Given a tuple, determine whether, as a result of the Head, personY or others will be affected as mentioned in the Tail or not. | Commonsense Classification | Sociology, Commonsense -> Concepts and Relations -> Social Commonsense | English | English |
task1197_atomic_classification_oreact |
Given a tuple, determine whether, as a result of the Head, personY or others feel what is mentioned in the Tail or not. | Commonsense Classification | Sociology, Commonsense -> Concepts and Relations -> Social Commonsense | English | English |
task1198_atomic_classification_owant |
Given a tuple, determine whether, as a result of the Head, personY or others will want what is mentioned in the Tail or not. | Commonsense Classification | Sociology, Commonsense -> Concepts and Relations -> Social Commonsense | English | English |
task1199_atomic_classification_xattr |
Given a tuple, determine whether, as a result of the Head, personX will be seen as what is mentioned in the Tail or not. | Commonsense Classification | Sociology, Commonsense -> Concepts and Relations -> Social Commonsense | English | English |
task1200_atomic_classification_xeffect |
Given a tuple, determine whether, as a result of the Head, personX will be affected as mentioned in the Tail or not. | Commonsense Classification | Sociology, Commonsense -> Concepts and Relations -> Social Commonsense | English | English |
task1201_atomic_classification_xintent |
Given a tuple, determine whether The tail is the intention of the PersonX from the Head or not. | Commonsense Classification | Sociology, Commonsense -> Concepts and Relations -> Social Commonsense | English | English |
task1202_atomic_classification_xneed |
Given a tuple, determine whether PersonX needs what is mentioned in the Tail before the Head or not. | Commonsense Classification | Sociology, Commonsense -> Concepts and Relations -> Social Commonsense | English | English |
task1203_atomic_classification_xreact |
Given a tuple, determine whether, as a result of the Head, personX feels what is mentioned in the Tail or not. | Commonsense Classification | Sociology, Commonsense -> Concepts and Relations -> Social Commonsense | English | English |
task1204_atomic_classification_hinderedby |
Given a tuple, determine whether the Head can be hindered by what is mentioned in the Tail or not. | Commonsense Classification | Sociology, Commonsense -> Concepts and Relations -> Social Commonsense | English | English |
task1205_atomic_classification_isafter |
Given a tuple, determine whether the Head happens after the Tail or not. | Commonsense Classification | Sociology, Commonsense -> Concepts and Relations -> Social Commonsense, Commonsense -> Concepts and Relations -> Spatial Commonsense | English | English |
task1206_atomic_classification_isbefore |
Given a tuple, determine whether the Head happens before the Tail or not. | Commonsense Classification | Sociology, Commonsense -> Concepts and Relations -> Social Commonsense, Commonsense -> Concepts and Relations -> Spatial Commonsense | English | English |
task1207_atomic_classification_atlocation |
Given a tuple, determine whether the Head is located or can be found at/in/on the Tail or not. | Commonsense Classification | Sociology, Commonsense -> Concepts and Relations -> Physical Commonsense, Commonsense -> Concepts and Relations -> Social Commonsense | English | English |
task1208_atomic_classification_xreason |
Given a tuple, determine whether The Tail is the reason for the Head or not. | Commonsense Classification | Sociology, Commonsense -> Concepts and Relations -> Social Commonsense | English | English |
task1209_atomic_classification_objectuse |
Given a tuple, determine whether the Head is used for the Tail or not. | Commonsense Classification | Sociology, Commonsense -> Concepts and Relations -> Physical Commonsense, Commonsense -> Concepts and Relations -> Social Commonsense | English | English |
task1210_atomic_classification_madeupof |
Given a tuple, determine whether the Head is made of the Tail or not. | Commonsense Classification | Sociology, Commonsense -> Concepts and Relations -> Physical Commonsense, Commonsense -> Concepts and Relations -> Social Commonsense | English | English |
task1211_atomic_classification_hassubevent |
Given a tuple, determine whether the Head includes an event or an action in the Tail or not. | Commonsense Classification | Sociology, Commonsense -> Concepts and Relations -> Physical Commonsense, Commonsense -> Concepts and Relations -> Social Commonsense | English | English |
task1212_atomic_classification_hasproperty |
Given a tuple, determine whether the Head can be characterized by being or having the Tail or not. | Commonsense Classification | Sociology, Commonsense -> Concepts and Relations -> Physical Commonsense | English | English |
task1213_atomic_classification_desires |
Given a tuple, determine whether the Head desires the Tail or not. | Commonsense Classification | Sociology, Commonsense -> Concepts and Relations -> Social Commonsense | English | English |
task1214_atomic_classification_xwant |
Given a tuple, determine whether, as a result of the Head, personX wants what is mentioned in the Tail or not. | Commonsense Classification | Sociology, Commonsense -> Concepts and Relations -> Social Commonsense | English | English |
task1215_atomic_classification_capableof |
Given a tuple, ddetermine whether the Head is capable of the Tail or not. | Commonsense Classification | Sociology, Commonsense -> Concepts and Relations -> Social Commonsense | English | English |
task1216_atomic_classification_causes |
Given a tuple, determine whether the Head causes the Tail or not. | Commonsense Classification | Sociology, Commonsense -> Concepts and Relations -> Social Commonsense | English | English |
task1217_atomic_answer_generation |
Given a sentence, fill in the blank with a plausible word. | Fill in The Blank | Sociology, Commonsense -> Concepts and Relations -> Physical Commonsense, Commonsense -> Concepts and Relations -> Social Commonsense | English | English |
task1218_ted_translation_en_ja |
Translate a sentence in English to Japanese. | Translation | TED Talks, Captions -> Video Captions | English | Japanese |
task1219_ted_translation_en_es |
Translate a sentence in English to Spanish. | Translation | TED Talks, Captions -> Video Captions | English | Spanish |
task1220_ted_translation_en_ar |
Translate a sentence in English to Arabic. | Translation | TED Talks, Captions -> Video Captions | English | Arabic |
task1221_ted_translation_en_he |
Translate a sentence in English to Hebrew. | Translation | TED Talks, Captions -> Video Captions | English | Hebrew |
task1222_ted_translation_ja_en |
Translate a sentence in Japanese to English. | Translation | TED Talks, Captions -> Video Captions | Japanese | English |
task1223_ted_translation_ja_es |
Translate a sentence in Japanese to Spanish. | Translation | TED Talks, Captions -> Video Captions | Japanese | Spanish |
task1224_ted_translation_ja_ar |
Translate a sentence in Japanese to Arabic. | Translation | TED Talks, Captions -> Video Captions | Japanese | Arabic |
task1225_ted_translation_ja_he |
Translate a sentence in Japanese to Hebrew. | Translation | TED Talks, Captions -> Video Captions | Japanese | Hebrew |
task1226_ted_translation_es_en |
Translate a sentence in Spanish to English. | Translation | TED Talks, Captions -> Video Captions | Spanish | English |
task1227_ted_translation_es_ja |
Translate a sentence in Spanish to Japanese. | Translation | TED Talks, Captions -> Video Captions | Spanish | Japanese |
task1228_ted_translation_es_ar |
Translate a sentence in Spanish to Arabic. | Translation | TED Talks, Captions -> Video Captions | Spanish | Arabic |
task1229_ted_translation_es_he |
Translate a sentence in Spanish to Hebrew. | Translation | TED Talks, Captions -> Video Captions | Spanish | Hebrew |
task1230_ted_translation_ar_en |
Translate a sentence in Arabic to English. | Translation | TED Talks, Captions -> Video Captions | Arabic | English |
task1231_ted_translation_ar_ja |
Translate a sentence in Arabic to Japanese. | Translation | TED Talks, Captions -> Video Captions | Arabic | Japanese |
task1232_ted_translation_ar_es |
Translate a sentence in Arabic to Spanish. | Translation | TED Talks, Captions -> Video Captions | Arabic | Spanish |
task1233_ted_translation_ar_he |
Translate a sentence in Arabic to Hebrew. | Translation | TED Talks, Captions -> Video Captions | Arabic | Hebrew |
task1234_ted_translation_he_en |
Translate a sentence in Hebrew to English. | Translation | TED Talks, Captions -> Video Captions | Hebrew | English |
task1235_ted_translation_he_ja |
Translate a sentence in Hebrew to Japanese. | Translation | TED Talks, Captions -> Video Captions | Hebrew | Japanese |
task1236_ted_translation_he_es |
Translate a sentence in Hebrew to Spanish. | Translation | TED Talks, Captions -> Video Captions | Hebrew | Spanish |
task1237_ted_translation_he_ar |
Translate a sentence in Hebrew to Arabic. | Translation | TED Talks, Captions -> Video Captions | Hebrew | Arabic |
task1238_ted_translation_gl_en |
Translate a sentence in Galician to English. | Translation | TED Talks, Captions -> Video Captions | Galician | English |
task1239_ted_translation_gl_ja |
Translate a sentence in Galician to Japanese. | Translation | TED Talks, Captions -> Video Captions | Galician | Japanese |
task1240_ted_translation_gl_es |
Translate a sentence in Galician to Spanish. | Translation | TED Talks, Captions -> Video Captions | Galician | Spanish |
task1241_ted_translation_gl_ar |
Translate a sentence in Galician to Arabic. | Translation | TED Talks, Captions -> Video Captions | Galician | Arabic |
task1242_ted_translation_gl_he |
Translate a sentence in Galician to Hebrew. | Translation | TED Talks, Captions -> Video Captions | Galician | Hebrew |
task1243_ted_translation_gl_it |
Translate a sentence in Galician to Italian. | Translation | TED Talks, Captions -> Video Captions | Galician | Italian |
task1244_ted_translation_gl_pl |
Translate a sentence in Galician to Polish. | Translation | TED Talks, Captions -> Video Captions | Galician | Polish |
task1245_ted_translation_gl_fa |
Translate a sentence in Galician to Farsi. | Translation | TED Talks, Captions -> Video Captions | Galician | Persian |
task1246_ted_translation_gl_pt |
Translate a sentence in Galician to Portugese. | Translation | TED Talks, Captions -> Video Captions | Galician | Portuguese |
task1247_ted_translation_it_en |
Translate a sentence in Italian to English. | Translation | TED Talks, Captions -> Video Captions | Italian | English |
task1248_ted_translation_it_ja |
Translate a sentence in Italian to Japanese. | Translation | TED Talks, Captions -> Video Captions | Italian | Japanese |
task1249_ted_translation_it_es |
Translate a sentence in Italian to Spanish. | Translation | TED Talks, Captions -> Video Captions | Italian | Spanish |
task1250_ted_translation_it_ar |
Translate a sentence in Italian to Arabic. | Translation | TED Talks, Captions -> Video Captions | Italian | Arabic |
task1251_ted_translation_it_he |
Translate a sentence in Italian to Hebrew. | Translation | TED Talks, Captions -> Video Captions | Italian | Hebrew |
task1252_ted_translation_it_gl |
Translate a sentence in Italian to Galician. | Translation | TED Talks, Captions -> Video Captions | Italian | Galician |
task1253_ted_translation_it_pl |
Translate a sentence in Italian to Polish. | Translation | TED Talks, Captions -> Video Captions | Italian | Polish |
task1254_ted_translation_it_fa |
Translate a sentence in Italian to Farsi. | Translation | TED Talks, Captions -> Video Captions | Italian | Persian |
task1255_ted_translation_it_pt |
Translate a sentence in Italian to Portugese. | Translation | TED Talks, Captions -> Video Captions | Italian | Portuguese |
task1256_ted_translation_pl_en |
Translate a sentence in Polish to English. | Translation | TED Talks, Captions -> Video Captions | Polish | English |
task1257_ted_translation_pl_ja |
Translate a sentence in Polish to Japanese. | Translation | TED Talks, Captions -> Video Captions | Polish | Japanese |
task1258_ted_translation_pl_es |
Translate a sentence in Polish to Spanish. | Translation | TED Talks, Captions -> Video Captions | Polish | Spanish |
task1259_ted_translation_pl_ar |
Translate a sentence in Polish to Arabic. | Translation | TED Talks, Captions -> Video Captions | Polish | Arabic |
task1260_ted_translation_pl_he |
Translate a sentence in Polish to Hebrew. | Translation | TED Talks, Captions -> Video Captions | Polish | Hebrew |
task1261_ted_translation_pl_gl |
Translate a sentence in Polish to Galician. | Translation | TED Talks, Captions -> Video Captions | Polish | Galician |
task1262_ted_translation_pl_it |
Translate a sentence in Polish to Italian. | Translation | TED Talks, Captions -> Video Captions | Polish | Italian |
task1263_ted_translation_pl_fa |
Translate a sentence in Polish to Farsi. | Translation | TED Talks, Captions -> Video Captions | Polish | Persian |
task1264_ted_translation_pl_pt |
Translate a sentence in Polish to Portugese. | Translation | TED Talks, Captions -> Video Captions | Polish | Portuguese |
task1265_ted_translation_fa_en |
Translate a sentence in Farsi to English. | Translation | TED Talks, Captions -> Video Captions | Persian | English |
task1266_ted_translation_fa_ja |
Translate a sentence in Farsi to Japanese. | Translation | TED Talks, Captions -> Video Captions | Persian | Japanese |
task1267_ted_translation_fa_es |
Translate a sentence in Farsi to Spanish. | Translation | TED Talks, Captions -> Video Captions | Persian | Spanish |
task1268_ted_translation_fa_ar |
Translate a sentence in Farsi to Arabic. | Translation | TED Talks, Captions -> Video Captions | Persian | Arabic |
task1269_ted_translation_fa_he |
Translate a sentence in Farsi to Hebrew. | Translation | TED Talks, Captions -> Video Captions | Persian | Hebrew |
task1270_ted_translation_fa_gl |
Translate a sentence in Farsi to Galician. | Translation | TED Talks, Captions -> Video Captions | Persian | Galician |
task1271_ted_translation_fa_it |
Translate a sentence in Farsi to Italian. | Translation | TED Talks, Captions -> Video Captions | Persian | Italian |
task1272_ted_translation_fa_pl |
Translate a sentence in Farsi to Polish. | Translation | TED Talks, Captions -> Video Captions | Persian | Polish |
task1273_ted_translation_fa_pt |
Translate a sentence in Farsi to Portugese. | Translation | TED Talks, Captions -> Video Captions | Persian | Portuguese |
task1274_ted_translation_pt_en |
Translate a sentence in Portugese to English. | Translation | TED Talks, Captions -> Video Captions | Portuguese | English |
task1275_ted_translation_pt_ja |
Translate a sentence in Portugese to Japanese. | Translation | TED Talks, Captions -> Video Captions | Portuguese | Japanese |
task1276_ted_translation_pt_es |
Translate a sentence in Portugese to Spanish. | Translation | TED Talks, Captions -> Video Captions | Portuguese | Spanish |
task1277_ted_translation_pt_ar |
Translate a sentence in Portugese to Arabic. | Translation | TED Talks, Captions -> Video Captions | Portuguese | Arabic |
task1278_ted_translation_pt_he |
Translate a sentence in Portugese to Hebrew. | Translation | TED Talks, Captions -> Video Captions | Portuguese | Hebrew |
task1279_ted_translation_pt_gl |
Translate a sentence in Portugese to Galician. | Translation | TED Talks, Captions -> Video Captions | Portuguese | Galician |
task1280_ted_translation_pt_it |
Translate a sentence in Portugese to Italian. | Translation | TED Talks, Captions -> Video Captions | Portuguese | Italian |
task1281_ted_translation_pt_pl |
Translate a sentence in Portugese to Polish. | Translation | TED Talks, Captions -> Video Captions | Portuguese | Polish |
task1282_ted_translation_pt_fa |
Translate a sentence in Portugese to Farsi. | Translation | TED Talks, Captions -> Video Captions | Portuguese | Persian |
task1283_hrngo_quality_classification |
Evaluate quality of system generated reference. | Text Quality Evaluation | Dialogue, Public Places -> Restaurants | English | English |
task1284_hrngo_informativeness_classification |
Evaluate informativeness of system generated reference. | Text Quality Evaluation | Dialogue, Public Places -> Restaurants | English | English |
task1285_kpa_keypoint_matching |
Given a depate topic, an argument on the topic and a keypoint, answer if the keypoint summarizes the argument | Text Matching | Reviews, Law, Dialogue, Government and Politics, Philosophy, World Religions | English | English |
task1286_openbookqa_question_answering |
Given a multiple-choice question and you have to pick the correct option. | Question Answering | Natural Science | English | English |
task1287_glue_qqp_paraphrasing |
Given two questions check if these questions have the same meaning. | Text Matching | Miscellaneous | English | English |
task1288_glue_mrpc_paraphrasing |
Given two sentences check if these questions have the same meaning. | Text Matching | News, Web | English | English |
task1289_trec_classification |
Given a question, detect which category better describes it. | Question Understanding | Miscellaneous | English | English |
task1290_xsum_summarization |
Given an article, summarize it. | Summarization | News | English | English |
task1291_multi_news_summarization |
Given some news, summarize them. | Summarization | News | English | English |
task1292_yelp_review_full_text_categorization |
Given a review about a place, provide a rating for it. | Sentiment Analysis | Reviews | English | English |
task1293_kilt_tasks_hotpotqa_question_answering |
Answer the given question. | Question Answering | Wikipedia | English | English |
task1294_wiki_qa_answer_verification |
Given a question and an answer, verify the answer. | Answer Verification | Wikipedia | English | English |
task1295_adversarial_qa_question_answering |
Given a question and a context, answer the question. | Question Answering | Wikipedia | English | English |
task1296_wiki_hop_question_answering |
Given a subject, a relation, and a context, find the object with that relation to the subject. | Question Answering | Wikipedia | English | English |
task1297_qasc_question_answering |
Given two facts, and a multiple-choice question, answer the question. | Question Answering | Natural Science -> School Science Textbooks | English | English |
task1308_amazonreview_category_classification |
You're given a review from Amazon and category of the product, classify whether category matchs the review. | Text Categorization | Reviews | English | English |
task1309_amazonreview_summary_classification |
You're given a review from Amazon and summary of the review, classify whether summary match the original review. | Summarization | Reviews | English | English |
task1310_amazonreview_rating_classification |
You're given a review from Amazon. Your task is to generate a rating for the product on a scale of 1-5 based on the review. | Sentiment Analysis | Reviews | English | English |
task1311_amazonreview_rating_classification |
You're given a review from Amazon and rating of the review, classify whether rating match the review. | Sentiment Analysis | Reviews | English | English |
task1312_amazonreview_polarity_classification |
You are given a review of Amazon's food products. Your task is to divide them into two classes: negative or positive. | Sentiment Analysis | Reviews | English | English |
task1313_amazonreview_polarity_classification |
You're given a review from Amazon and polarity of the review, classify whether review match the polarity. | Sentiment Analysis | Reviews | English | English |
task1314_country_abbreviation |
Given a country name, return the abbrevation name of the given country | Misc. | Countries | English | English |
task1315_find_range_array |
Given a list of integers, find the range of the list | Program Execution | Mathematics | English | English |
task1316_remove_duplicates_string |
Given a string, remove all the duplicate characters from the string | Program Execution | Mathematics | English | English |
task1317_country_calling_code |
Given a country name, return the calling code of the given country | Misc. | Countries | English | English |
task1318_country_national_dish |
Given a country name, return the national dish name of the given country | Misc. | Countries | English | English |
task1319_country_by_barcode_prefix |
Given a country name, return the barcode prefix of the given country | Misc. | Countries | English | English |
task1320_country_domain_tld |
Given a country name, return the Top Level Domain (TLD) of the given country | Misc. | Countries | English | English |
task1321_country_continent |
Given a country name, return the continent name of the given country | Misc. | Countries | English | English |
task1322_country_government_type |
Given a country name, return the government type of the given country | Misc. | Countries | English | English |
task1323_open_subtitles_hi_en_translation |
Translating Hindi to English (based on Open Subtitles) | Translation | Commonsense -> Concepts and Relations, Dialogue, Narrative | Hindi | English |
task1324_open_subtitles_te_en_translation |
Translating Telugu to English (based on Open Subtitles) | Translation | Commonsense -> Concepts and Relations, Dialogue, Narrative | Telugu | English |
task1325_qa_zre_question_generation_on_subject_relation |
Generating questions by including a specific subject and certain relation to Context (based on qa_zre dataset) | Question Generation | Wikipedia | English | English |
task1326_qa_zre_question_generation_from_answer |
Generating questions from answers (based on qa_zre dataset) | Question Generation | Wikipedia | English | English |
task1327_qa_zre_answer_generation_from_question |
Generating answers from questions (based on qa_zre dataset) | Question Answering | Wikipedia | English | English |
task1328_qa_zre_relation_generation_from_question |
Classify relation between question and context (based on qa_zre dataset) | Question Understanding | Wikipedia | English | English |
task1329_open_subtitles_en_hi_translation |
Translating English to Hindi (based on Open Subtitles) | Translation | Narrative, Dialogue, Commonsense -> Concepts and Relations | English | Hindi |
task1330_open_subtitles_en_te_translation |
Translating English to Telugu (based on Open Subtitles) | Translation | Narrative, Dialogue, Commonsense -> Concepts and Relations | English | Telugu |
task1331_reverse_array |
Given a list of integers, reverse the order of the items in the list | Program Execution | Mathematics | English | English |
task1332_check_leap_year |
Given a year, check if it is a leap year or not | Misc. | Mathematics | English | English |
task1333_check_validity_date_ddmmyyyy |
Given a date in dd/mm/yyyy format, check if it is a valid date or not | Misc. | Mathematics, Commonsense -> Concepts and Relations | English | English |
task1334_sqac_answer_generation |
Generating answers to SQAC questions | Question Answering | Wikipedia, News | Spanish | Spanish |
task1335_sqac_question_generation |
Classifying race of speaker of sentence | Question Generation | Wikipedia, News | Spanish | Spanish |
task1336_peixian_equity_evaluation_corpus_gender_classifier |
Classifying gender of speaker of sentence | Gender Classification | Commonsense, Dialogue, Narrative | English | English |
task1338_peixian_equity_evaluation_corpus_sentiment_classifier |
Classifying the sentiment within the sentence | Sentiment Analysis | Commonsense, Dialogue, Narrative | English | English |
task1339_peixian_equity_evaluation_corpus_text_completion |
Replacing blanks within text for an emption | Fill in The Blank | Commonsense, Dialogue, Narrative | English | English |
task1340_msr_text_compression_compression |
Generating Compressed text based on MSR dataset | Sentence Compression | News, Dialogue, Miscellaneous | English | English |
task1341_msr_text_classification |
Generating Classification of text in MSR dataset | Text Quality Evaluation | News, Dialogue, Miscellaneous | English | English |
task1342_amazon_us_reviews_title |
Generating Title for Amazon US review dataset | Title Generation | Reviews | English | English |
task1343_amazon_us_reviews_rating |
Generating Rating for Amazon US review dataset | Sentiment Analysis | Reviews | English | English |
task1344_glue_entailment_classification |
Checking if the second sentance entails the first or not | Textual Entailment | Books, Dialogue | English | English |
task1345_glue_qqp_question_paraprashing |
Paraphrasing a question to generate a similar question | Question Rewriting | Books, Dialogue | English | English |
task1346_glue_cola_grammatical_correctness_classification |
Checking grammatical correctness of a statement. | Grammar Error Detection | Books, Dialogue | English | English |
task1347_glue_sts-b_similarity_classification |
Classifying two sentence based on semantic similarity on the scale of 0 - 5. | Text Matching | Books, Dialogue | English | English |
task1350_opus100_translation_en_gu |
Translate a sentence in English to Gujarati | Translation | Books, Miscellaneous | English | Gujarati |
task1351_opus100_translation_gu_en |
Translate a sentence in Gujarati to English | Translation | Books, Miscellaneous | Gujarati | English |
task1352_hind_encorp_translation_hi_en |
Translate a sentence in Hindi to English | Translation | Books, News, Wikipedia, Miscellaneous | Hindi | English |
task1353_hind_encorp_translation_en_hi |
Translate a sentence in English to Hindi | Translation | Books, News, Wikipedia, Miscellaneous | English | Hindi |
task1354_sent_comp_classification |
Given text and headline classify if headline matches text or not | Text Matching | News | English | English |
task1355_sent_comp_summarization |
Given text generate summary about the text | Summarization | News | English | English |
task1356_xlsum_title_generation |
Generating title for the text in xlsum | Title Generation | News | English | English |
task1357_xlsum_summary_generation |
Generating summary for the text in xlsum | Summarization | News | English | English |
task1358_xlsum_title_generation |
Generates title for the text in xlsum | Title Generation | News | English | English |
task1359_numer_sense_answer_generation |
Generates answer to numer sense | Fill in The Blank | Commonsense -> Concepts and Relations, Animals | English | English |
task1360_numer_sense_multiple_choice_qa_generation |
Generating answers to numer sense | Fill in The Blank | Commonsense -> Concepts and Relations, Animals | English | English |
task1361_movierationales_classification |
Classification (based on Movie Rationales) | Sentiment Analysis | Reviews -> Movies, Movies | English | English |
task1364_hans_answer_generation |
Generating answers (based on Hans) | Sentence Composition | Reviews -> Movies, Movies | English | English |
task1365_opustedtalks_translation |
Translation from English to Croatian using Opus_Ted Dataset | Translation | TED Talks, Captions -> Video Captions | English | Croatian |
task1366_healthfact_classification |
Find if claim belongs to a predefined category using given paragraph | Fact Verification | Healthcare | English | English |
task1367_opustedtalks_translation |
Translation from Croatian to English using Opus_Ted Dataset | Translation | TED Talks, Captions -> Video Captions | Croatian | English |
task1368_healthfact_sentence_generation |
Generate a claim based on a given paragraph | Sentence Composition | Healthcare | English | English |
task1369_healthfact_sentence_generation |
Generate an explanation for a claim based on a given paragraph | Explanation | Healthcare | English | English |
task1370_newscomm_classification |
Classifying the language of given statement | Language Identification | News | English, French, Arabic, Czech, German, Spanish, Dutch, Portuguese, Italian, Zhuang, Japanese, Russian | English |
task1371_newscomm_translation |
Translating news commentaries given in English to French language based on the news_Commentary dataset | Translation | News | English | French |
task1373_newscomm_translation |
Translating news commentaries given in German to Spanish language based on the news_Commentary dataset | Translation | News | German | Spanish |
task1374_newscomm_translation |
Translating news commentaries given in Arabic to Czeck language based on the news_Commentary dataset | Translation | News | Arabic | Czech |
task1375_newscomm_translation |
Translating news commentaries given in Dutch to Portuguese language based on the news_Commentary dataset | Translation | News | Dutch | Portuguese |
task1376_newscomm_translation |
Translating news commentaries given in Italian to Zhuang language based on the news_Commentary dataset | Translation | News | Italian | Zhuang |
task1377_newscomm_translation |
Translating news commentaries given in French to Russian language based on the news_Commentary dataset | Translation | News | French | Russian |
task1378_quarel_correct_answer_generation |
Given a sentence and a question, write the correct answer based on the sentence. | Question Answering | Story, Commonsense -> Concepts and Relations | English | English |
task1379_quarel_incorrect_answer_generation |
Given a sentence and a question, write the incorrect answer based on the sentence. | Wrong Candidate Generation | Story, Commonsense -> Concepts and Relations | English | English |
task1380_quarel_correct_option_generation |
Given a sentence and a question, choose the correct option number instead of exact answer based on the sentence. | Question Answering | Story, Commonsense -> Concepts and Relations | English | English |
task1381_quarel_incorrect_option_generation |
Given a sentence and a question, choose the incorrect option number instead of exact answer based on the sentence. | Wrong Candidate Generation | Story, Commonsense -> Concepts and Relations | English | English |
task1382_quarel_write_correct_answer |
Writing a correct answer to a given question based on a given sentence. | Question Answering | Story, Commonsense -> Concepts and Relations | English | English |
task1383_quarel_write_incorrect_answer |
Writing a incorrect answer to a given question based on a given sentence. | Wrong Candidate Generation | Story, Commonsense -> Concepts and Relations | English | English |
task1384_deal_or_no_dialog_classification |
Given a dialogue, classify whether both participants agree to the deal | Dialogue State Tracking | Dialogue, Commonsense -> Concepts and Relations -> Social Commonsense | English | English |
task1385_anli_r1_entailment |
Given a premise and hypothesis, determine if the hypothesis entails, contradicts, or is neutral to the premise. | Textual Entailment | Miscellaneous | English | English |
task1386_anli_r2_entailment |
Given a premise and hypothesis, determine if the hypothesis entails, contradicts, or is neutral to the premise. | Textual Entailment | Miscellaneous | English | English |
task1387_anli_r3_entailment |
Given a premise and hypothesis, determine if the hypothesis entails, contradicts, or is neutral to the premise. | Textual Entailment | Miscellaneous | English | English |
task1388_cb_entailment |
Given a premise and hypothesis, determine if the hypothesis entails, contradicts, or is neutral to the premise. | Textual Entailment | Dialogue | English | English |
task1389_hellaswag_completion |
Given a context and four options, pick the best ending for the context. | Text Completion | Captions -> Video Captions | English | English |
task1390_wscfixed_coreference |
Given a context, a pronoun, and a noun, determine if the pronoun in the context refers to the noun or not. | Coreference Resolution | Fiction, Books | English | English |
task1391_winogrande_easy_answer_generation |
Answering a fill in the blank question on objects. | Coreference Resolution | Commonsense -> Concepts and Relations -> Social Commonsense, Commonsense -> Concepts and Relations -> Physical Commonsense | English | English |
task1392_superglue_multirc_answer_verification |
Given a context passage, a question about that paragraph, and a possible answer to that question, verify the answer. | Answer Verification | Fiction, History, News | English | English |
task1393_superglue_copa_text_completion |
Given a premise sentence, two possible options and a question word, choose the best option. | Cause Effect Classification | Web | English | English |
task1394_meta_woz_task_classification |
Given two task sentences, detect the domains of the task | Dialogue Act Recognition | Dialogue, Commonsense -> Concepts and Relations -> Social Commonsense | English | English |
task1395_europa_ecdc_tm_en_sv_translation |
Translate English sentences to Swedish | Translation | Healthcare, Professions | English | Swedish |
task1396_europa_ecdc_tm_en_de_translation |
Translate English sentences to German | Translation | Healthcare, Professions | English | German |
task1397_europa_ecdc_tm_fr_en_translation |
Translate French sentences to English | Translation | Healthcare, Professions | French | English |
task1398_obqa_question_generation |
Given a fact, generate a question that can be answered using the fact | Question Generation | Natural Science -> School Science Textbooks | English | English |
task1399_obqa_answer_generation |
Given a fact and question, generate an answer to the question | Question Answering | Natural Science -> School Science Textbooks | English | English |
task1400_obqa_incorrect_answer_generation |
Given a fact and question, generate an incorrect answer to the question | Wrong Candidate Generation | Natural Science -> School Science Textbooks | English | English |
task1401_obqa_sentence_generation |
Given a question and answer pair, generate a fact statement | Sentence Composition | Natural Science -> School Science Textbooks | English | English |
task1402_clue_question_generation |
Given a Chinese passage, generate a question based on the passage | Question Generation | Wikipedia | Chinese | Chinese |
task1403_check_validity_date_mmddyyyy |
Given a date in mm/dd/yyyy format, check if it is a valid date or not | Misc. | Commonsense -> Concepts and Relations | English | English |
task1404_date_conversion |
Given a date in a particular format, convert it into some other format | Program Execution | Commonsense -> Concepts and Relations | English | English |
task1405_find_median |
Given a list of integers, find the median of the input list | Program Execution | Mathematics, Statistics | English | English |
task1406_kth_smallest_element |
Given a list of integers and an integer k, find the kth smallest element in the list | Program Execution | Mathematics, Statistics | English | English |
task1407_dart_question_generation |
Generate fill-in-the-blank style questions from RDF triplets of the DART dataset | Data to Text | Wikipedia | English | English |
task1408_dart_similarity_classification |
Classify whether two sentences (from DART) are similar or not based on their relationships | Text Matching | Wikipedia | English | English |
task1409_dart_text_generation |
Generating sentences based on DART RDF relationships | Data to Text | Wikipedia | English | English |
task1410_dart_relationship_extraction |
Extracting RDF relationships from DART sentences | Information Extraction | Wikipedia | English | English |
task1411_dart_subject_identification |
Given a sentence (from DART), identify the subject of the sentence | Information Extraction | Wikipedia | English | English |
task1412_web_questions_question_answering |
Answer the given question | Question Answering | Knowledge Base -> Freebase | English | English |
task1413_dart_object_identification |
Given a sentence (from DART), identify the object of the sentence | Information Extraction | Wikipedia | English | English |
task1414_ajgt_twitter_ar_classification |
Classify Arabic tweets (based on ajgt_twitter_ar) as having positive or negative sentiment |
Sentiment Analysis | Social Media -> Twitter | Arabic | English |
task1415_youtube_caption_corrections_grammar_correction |
Given a set of closed captions (from youtube_caption_corrections), produce a grammatically correct version of those captions |
Grammar Error Correction | Computer Science -> Machine Learning, Captions -> Video Captions | English | English |
task1416_youtube_caption_corrections_incorrect_grammar_classification |
Given a set of closed captions (from youtube_caption_corrections), classify which words are grammatically incorrect |
Grammar Error Detection | Computer Science -> Machine Learning, Captions -> Video Captions | English | English |
task1418_bless_semantic_relation_classification |
Given a pair of words, deduce the type of relationship between them | Word Relation Classification | Animals, Commonsense | English | English |
task1419_mathqa_gain |
Given a math problem on gain and options to choose from, find the correct option that answers the problem | Question Answering | Mathematics | English | English |
task1420_mathqa_general |
Given a general math problem and options to choose from, find the correct option that answers the problem | Question Answering | Mathematics | English | English |
task1421_mathqa_other |
Given a math problem and options to choose from, find the correct option that answers the problem | Question Answering | Mathematics | English | English |
task1422_mathqa_physics |
Given a problem on physics and options to choose from, find the correct option that answers the problem | Question Answering | Physics | English | English |
task1423_mathqa_geometry |
Given a problem on geometry and options to choose from, find the correct option that answers the problem | Question Answering | Mathematics | English | English |
task1424_mathqa_probability |
Given a problem on probability and options to choose from, find the correct option that answers the problem | Question Answering | Mathematics | English | English |
task1425_country_iso_numeric |
Given a country name, return the numeric ISO of the given country | Misc. | Countries | English | English |
task1426_country_independence_year |
Given a country name, return the year of independence of the given country | Misc. | Countries | English | English |
task1427_country_region_in_world |
Given a country name, return the located region in the world map of the given country | Misc. | Countries | English | English |
task1428_country_surface_area |
Given a country name, return the surface area in square-kilometer of the given country | Misc. | Countries | English | English |
task1429_evalution_semantic_relation_classification |
Given a pair of words, deduce the type of relationship between them | Word Relation Classification | Commonsense | English | English |
task1431_head_qa_answer_generation |
Answering a multiple-choice question | Question Answering | Healthcare | English | English |
task1432_head_qa_language_translation_en_to_es |
Translation from English to Spanish | Translation | Healthcare | English | Spanish |
task1433_head_qa_language_translation_es_to_en |
Translation from Spanish to English | Translation | Healthcare | Spanish | English |
task1434_head_qa_classification |
Classifying questions into topics | Text Categorization | Healthcare | English | English |
task1435_ro_sts_parallel_language_translation_ro_to_en |
Translation from Romanian to English | Translation | Commonsense | Romanian | English |
task1436_ro_sts_parallel_language_translation_en_to_ro |
Translation from English to Romanian | Translation | Commonsense | English | Romanian |
task1437_doqa_cooking_question_generation |
Given a paragraph about cooking, and a set of conversational question answers about the paragraph, generate a relevant question to the topic of the paragraph | Question Generation | Nutrition, Dialogue, Food | English | English |
task1438_doqa_cooking_answer_generation |
Given a paragraph about cooking, and a set of conversational question answers about the paragraph, answer a follow-up question from the paragraph | Question Answering | Nutrition, Dialogue, Food | English | English |
task1439_doqa_cooking_isanswerable |
Given a paragraph about cooking, and a set of conversational question answers about the paragraph, say whether the follow-up question can be answered from the passage | Answerability Classification | Nutrition, Dialogue, Food | English | English |
task1440_doqa_movies_question_generation |
Given a paragraph about movies, and a set of conversational question answers about the paragraph, generate a relevant question to the topic of the paragraph | Question Generation | Movies, Dialogue | English | English |
task1441_doqa_movies_answer_generation |
Given a paragraph about movies, and a set of conversational question answers about the paragraph, answer a follow-up question from the paragraph | Question Answering | Movies, Dialogue | English | English |
task1442_doqa_movies_isanswerable |
Given a paragraph about movies, and a set of conversational question answers about the paragraph, say whether the follow-up question can be answered from the passage | Answerability Classification | Movies, Dialogue | English | English |
task1443_string_to_number |
Given a string of spelled out digits return the number the string represents | Program Execution | Mathematics | English | English |
task1444_round_power_of_two |
Given a list of integers round them to the nearest power of two | Program Execution | Mathematics | English | English |
task1445_closest_integers |
Given a list of integers return the difference between the two closest integers | Program Execution | Mathematics | English | English |
task1446_farthest_integers |
Given a list of integers return the difference between the two farthest integers | Program Execution | Mathematics | English | English |
task1447_drug_extraction_ade |
Given a sentence from the ADE dataset, return the list of tokens that mentions names of the drugs or medicines from the ADE Dataset. | Named Entity Recognition | Biology -> Clinical Knowledge, Healthcare | English | English |
task1448_disease_entity_extraction_ncbi_dataset |
Given a sentence from the NCBI dataset, return the list of tokens that mentions names of the diseases or disorders from the NCBI Dataset. | Named Entity Recognition | Biology -> Clinical Knowledge, Healthcare | English | English |
task1449_disease_entity_extraction_bc5cdr_dataset |
Given a sentence from the BC5CDR dataset, return the list of tokens that mentions names of the diseases or disorders from the BC5CDR Dataset. | Named Entity Recognition | Biology -> Clinical Knowledge, Healthcare | English | English |
task1451_drug_dose_extraction |
Given a sentence and a drug from the ADE dataset, return the list of tokens that mentions of dose of that particular drug. | Information Extraction | Biology -> Clinical Knowledge, Healthcare | English | English |
task1452_location_entity_extraction_btc_corpus |
Given a sentence from the BTC dataset, return the list of tokens that mentions of locations/places. | Named Entity Recognition | Geography, Social Media -> Twitter | English | English |
task1453_person_entity_extraction_btc_corpus |
Given a sentence from the BTC dataset, return the list of tokens that mentions of person names. | Named Entity Recognition | Commonsense -> Concepts and Relations -> Social Commonsense, Social Media -> Twitter | English | English |
task1479_organization_entity_extraction_btc_corpus |
Given a sentence from the BTC dataset, return the list of tokens that mentions of companies or organizations. | Named Entity Recognition | Commonsense -> Concepts and Relations -> Social Commonsense, Professions, Social Media -> Twitter | English | English |
task1480_gene_extraction_jnlpba_dataset |
Given a sentence from the JNLPBA dataset, return the list of tokens that mentions of genes or proteins. | Named Entity Recognition | Biology -> Bioinformatics | English | English |
task1481_gene_extraction_bc2gm_dataset |
Given a sentence from the BC2GM dataset, return the list of tokens that mentions of genes or proteins. | Named Entity Recognition | Biology -> Bioinformatics | English | English |
task1482_gene_extraction_chemprot_dataset |
Given a sentence from the ChemProt dataset, return the list of tokens that mentions of protein. | Named Entity Recognition | Biology -> Bioinformatics | English | English |
task1483_chemical_extraction_chemprot_dataset |
Given a sentence from the ChemProt dataset, return the list of tokens that mentions of chemical substances. | Named Entity Recognition | Chemistry | English | English |
task1484_gene_extraction_linnaeus_dataset |
Given a sentence from the Linnaues dataset, return the list of tokens that mentions of genes. | Named Entity Recognition | Biology -> Bioinformatics | English | English |
task1485_organ_extraction_anem_dataset |
Given a sentence from the AnEM dataset, return the list of tokens that mentions of organs in the body. | Named Entity Recognition | Biology -> Clinical Knowledge | English | English |
task1486_cell_extraction_anem_dataset |
Given a sentence from the AnEM dataset, return the list of tokens that mentions of cells in the body. | Named Entity Recognition | Biology -> Clinical Knowledge | English | English |
task1487_organism_substance_extraction_anem_dataset |
Given a sentence from the AnEM dataset, return the list of tokens that mentions of organs in the body. | Named Entity Recognition | Biology -> Clinical Knowledge | English | English |
task1488_sarcasmdetection_headline_classification |
Given a news headline in English, classify whether it is sarcastic or non-sarcastic in nature. | Text Categorization | News | English | English |
task1489_sarcasmdetection_tweet_classification |
Given a twitter in English, classify whether it is sarcastic or non-sarcastic in nature. | Text Categorization | Social Media -> Twitter | English | English |
task1490_bengali_personal_hate_speech_binary_classification |
Given a hateful post in Bengali, classify whether it is personal or non-personal in nature. | Text Categorization | Social Media, Dialogue | Bengali | English |
task1491_bengali_political_hate_speech_binary_classification |
Given a hateful post in Bengali, classify whether it is political or non-political in nature. | Text Categorization | Social Media, Dialogue | Bengali | English |
task1492_bengali_religious_hate_speech_binary_classification |
Given a hateful post in Bengali, classify whether it is religious or non-religious in nature. | Text Categorization | Social Media, Dialogue | Bengali | English |
task1493_bengali_geopolitical_hate_speech_binary_classification |
Given a hateful post in Bengali, classify whether it is geopolitical or non-geopolitical in nature. | Text Categorization | Social Media, Dialogue | Bengali | English |
task1494_bengali_hate_speech_classification |
Given a hateful post in Bengali, classify whether it is political, geopolitical, religious or personal in nature. | Text Categorization | Social Media, Dialogue | Bengali | English |
task1495_adverse_drug_event_classification |
Given a sentence, classify whether it contains any adverse drug event. | Text Categorization | Biology -> Clinical Knowledge, Healthcare | English | English |
task1496_bengali_reviews_sentiment_classification |
Given a restaurant review in Bengali, classify whether the sentiment is positive or negative. | Sentiment Analysis | Public Places -> Restaurants, Reviews -> Restaurants | Bengali | English |
task1497_bengali_book_reviews_sentiment_classification |
Given a book review in Bengali, classify whether the sentiment is positive or negative. | Sentiment Analysis | Books, Reviews -> Books | Bengali | English |
task1498_24hour_to_12hour_clock |
Given a timestamp in 24-hour format, convert it to 12-hour format | Misc. | Commonsense -> Concepts and Relations | English | English |
task1499_dstc3_summarization |
Summarization of conversations in DSTC 3 | Summarization | Public Places, Dialogue | English | English |
task1500_dstc3_classification |
Classification of Price Range in conversations in DSTC 3 | Dialogue State Tracking | Public Places, Dialogue | English | English |
task1501_dstc3_answer_generation |
Generating answers to DSTC 3 conversations related questions | Dialogue State Tracking | Public Places, Dialogue | English | English |
task1502_hatexplain_classification |
Classification of type of tweet in Hatexplain | Toxic Language Detection | Social Media -> Twitter | English | English |
task1503_hatexplain_classification |
Identification of target community in tweet in Hatexplain | Toxic Language Detection | Social Media -> Twitter | English | English |
task1504_hatexplain_answer_generation |
Passage Selection of offensive or hate speech phrases in tweets is Hatexplain | Toxic Language Detection | Social Media -> Twitter | English | English |
task1505_root09_semantic_relation_classification |
Given a pair of words, deduce the type of relationship between them | Word Relation Classification | Commonsense -> Concepts and Relations | English | English |
task1506_celebrity_minimal_dob_span |
Find the date of birth of a celebrity given a sentence bio | Information Extraction | Pop Culture | English | English |
task1507_boolean_temporal_reasoning |
Given a statement about date and time values, deduce whether it is true or false | Misc. | Commonsense -> Concepts and Relations | English | English |
task1508_wordnet_antonyms |
Given an adjective, generate its antonym | Word Semantics | Global Facts | English | English |
task1509_evalution_antonyms |
Given a word generate its antonym | Word Semantics | Global Facts | English | English |
task1510_evalution_relation_extraction |
Given a phrase describing the relationship between two words, extract the words and the lexical relationship between them | Information Extraction | Global Facts | English | English |
task1514_flores_translation_entone |
Translate from English to Nepali | Translation | Wikipedia | English | Nepali |
task1515_imppres_longtextgeneration |
Given a premise, generate hypothesis | Sentence Composition | Commonsense | English | English |
task1516_imppres_naturallanguageinference |
Classify a given premise and hypothesis pair | Textual Entailment | Commonsense | English | English |
task1517_limit_classfication |
Classifying sentence based on the condition that it contains a motion of a physical entity or not. | Information Extraction | News, Wikipedia | English | English |
task1518_limit_answer_generation |
Identifying the entities in a sentence where these entities take part in a physical motion. | Information Extraction | News, Wikipedia | English | English |
task1519_qa_srl_question_generation |
Using given sentence and a verb,generating questions which can be answered from the sentence. | Question Generation | News, Wikipedia | English | English |
task1520_qa_srl_answer_generation |
Generating answers to the questions based on the given sentence | Question Answering | News, Wikipedia | English | English |
task1529_scitail1.1_classification |
Determining if there is entailment between Hypothesis and Premise | Textual Entailment | Natural Science | English | English |
task1530_scitail1.1_sentence_generation |
Generating a Premise that entails the Hypothesis | Sentence Composition | Natural Science | English | English |
task1531_daily_dialog_type_classification |
Classify the input sentence into one of the 5 classes : unknown, commissive, question, information, directive | Dialogue Act Recognition | Dialogue | English | English |
task1532_daily_dialog_emotion_classification |
Classify the conversation sentences of input passage into the following emotions: anger, disgust, fear, happiness, sadness, No emotion | Sentiment Analysis | Dialogue | English | English |
task1533_daily_dialog_formal_classification |
Classify the conversation sentences of input passage into the following outputs: formal and informal | Dialogue Act Recognition | Dialogue | English | English |
task1534_daily_dialog_question_classification |
Classify if the first sentence of a conversation is a question | Dialogue Act Recognition | Dialogue | English | English |
task1535_daily_dialog_uniqueness_classification |
Classify if the conversation sentences of the input passage convey more than 2 unique emotions | Sentiment Analysis | Dialogue | English | English |
task1536_daily_dialog_happiness_classification |
Classify if the conversation sentences of the input passage convey only happiness emotion or not. | Sentiment Analysis | Dialogue | English | English |
task1537_tamil_offenseval_dravidian_classification |
Given a statement in Tamil, classify whether it is offensive or not | Toxic Language Detection | Social Media | Tamil | English |
task1538_malayalam_offenseval_dravidian_classification |
Given a statement in Malayalam, classify whether it is offensive or not | Toxic Language Detection | Social Media | Malayalam | English |
task1539_kannada_offenseval_dravidian_classification |
Given a statement in Kannada, classify whether it is offensive or not | Toxic Language Detection | Social Media | Kannada | English |
task1540_parsed_pdfs_summarization |
Given a text, generate a title for it | Title Generation | Computer Science | English | English |
task1541_agnews_classification |
Given a short article, classify the article based on its category | Text Categorization | News | English | English |
task1542_every_ith_element_from_starting |
Given a list return every ith element of the list starting from the 1st element | Program Execution | Code | English | English |
task1543_conll2002_parts_of_speech_tagging_answer_generation |
Given a question in Dutch language, write the part-of-speech tag for each word in the question | Pos Tagging | Miscellaneous | Dutch | Dutch, English |
task1544_conll2002_named_entity_recognition_answer_generation |
Given a question in Dutch language, write the named entities from the question if present | Named Entity Recognition | Miscellaneous | Dutch | Dutch, English |
task1545_conll2002_person_name_extraction_answer_generation |
Given a question in Dutch language, write the named entities from the question if present | Named Entity Recognition | Miscellaneous | Dutch | Dutch, English |
task1546_conll2002_location_name_extraction_answer_generation |
Given a question in Dutch language, write the location names from the question if present | Named Entity Recognition | Miscellaneous | Dutch | Dutch, English |
task1548_wiqa_binary_classification |
Binary Classification (based on steps in wiqa) | Sentence Ordering | Natural Science | English | English |
task1549_wiqa_answer_generation_missing_step |
Generating answer to place missing step in a series (based on wiqa) | Sentence Ordering | Natural Science | English | English |
task1551_every_ith_element_from_kth_element |
Given a list return every ith element of the list starting from the kth element | Program Execution | Mathematics | English | English |
task1552_scitail_question_generation |
Generating questions (based on SciTail) | Question Generation | Web, Natural Science -> School Science Textbooks | English | English |
task1553_cnn_dailymail_summarization |
Generating summary to news articles | Summarization | News | English | English |
task1554_scitail_classification |
Classifying supporting and non supporting statements from SciTail | Textual Entailment | Web, Natural Science -> School Science Textbooks | English | English |
task1555_scitail_answer_generation |
Generating answers to SciTail Sentence-Questions | Question Answering | Web, Natural Science -> School Science Textbooks | English | English |
task1556_scitail_passage_generation |
Generating passage based on SciTail Question-Answer | Sentence Composition | Web, Natural Science -> School Science Textbooks | English | English |
task1557_jfleg_answer_generation |
Generating answers (based on jfleg) | Grammar Error Correction | English Exams, Miscellaneous | English | English |
task1558_jfleg_incorrect_answer_generation |
Generating incorrect answers (based on jfleg) | Wrong Candidate Generation | English Exams, Miscellaneous | English | English |
task1559_blimp_binary_classification |
Classifying sentences (based on Blimp) | Linguistic Probing | Linguistics | English | English |
task1560_blimp_binary_classification |
Classifying sentences (based on Blimp) | Linguistic Probing | Linguistics | English | English |
task1561_clickbait_new_bg_summarization |
Providing a title summary to passage from Clickbait_new_bg dataset | Title Generation | News | Bulgarian | Bulgarian |
task1562_zest_text_modification |
Paraphrase the given question. | Question Rewriting | Government and Politics | English | English |
task1564_triviaqa_answer_generation |
Generating answers to questions in TriviaQA dataset | Question Answering | Web, Wikipedia | English | English |
task1565_triviaqa_classification |
Finding answer to multiple choice questions in TriviaQA dataset | Question Answering | Web, Wikipedia | English | English |
task1566_propara_structured_text_generation |
Generate entities from given text | Named Entity Recognition | Natural Science | English | English |
task1567_propara_question_generation |
Generate question from the given passage | Question Generation | Natural Science | English | English |
task1568_propara_classification |
Based on the passage, event, and entity, classify locations | Information Extraction | Natural Science | English | English |
task1569_cmrc2018_question_generation |
Generate question from the given passage | Question Generation | Wikipedia | Chinese | Chinese |
task1570_cmrc2018_answer_generation |
Generate the right answer to a given question from the context passage | Question Answering | Wikipedia | Chinese | Chinese |
task1571_cmrc2018_answer_generation_starting_index |
Generate starting index of the answer span to a given question from the context passage | Misc. | Wikipedia | Chinese | English |
task1572_samsum_summary |
Generate a summary of given conversations | Summarization | Dialogue, Commonsense -> Concepts and Relations -> Social Commonsense | English | English |
task1573_samsum_classification |
Classify whether given two dialogue sentences are sequential or not | Coherence Classification | Dialogue, Commonsense -> Concepts and Relations -> Social Commonsense | English | English |
task1574_amazon_reviews_multi_language_identification |
Classification of product review language | Language Identification | Reviews | English, Japanese, German, French, Chinese, Spanish | English |
task1575_amazon_reviews_multi_sentiment_classification |
Classification of product reviews into good or bad | Sentiment Analysis | Reviews | English, Japanese, German, French, Chinese, Spanish | English |
task1576_amazon_reviews_multi_english_language_classification |
Classification of reviews based on whether it is English or not | Language Identification | Reviews | English, Japanese, German, French, Chinese, Spanish | English |
task1577_amazon_reviews_multi_japanese_language_classification |
Classification of reviews based on whether it is Japanese or not | Language Identification | Reviews | English, Japanese, German, French, Chinese, Spanish | English |
task1579_gigaword_incorrect_summarization |
Generating incorrect summary to gigaword passages | Summarization | News | English | English |
task1580_eqasc-perturbed_question_generation |
Generating questions for eQASC facts | Question Generation | Natural Science -> School Science Textbooks | English | English |
task1581_eqasc-perturbed_answer_generation |
Generating answers for eQASC facts and questions | Question Answering | Natural Science -> School Science Textbooks | English | English |
task1582_bless_hypernym_generation |
Given a concept word, generate a hypernym for it | Word Semantics | Miscellaneous | English | English |
task1583_bless_meronym_classification |
Given an object and a part, decide whether the object has that part | Word Relation Classification | Miscellaneous | English | English |
task1584_evalution_meronym_classification |
Given an object and a part, decide whether the object has that part | Word Relation Classification | Miscellaneous | English | English |
task1585_root09_hypernym_generation |
Given a concept word, generate a hypernym for it | Word Semantics | Miscellaneous | English | English |
task1586_scifact_title_generation |
Title Generation | Title Generation | Scientific Research Papers | English | English |
task1587_scifact_classification |
Classification | Text Matching | Scientific Research Papers | English | English |
task1588_tecla_classification |
Classification | Text Categorization | News | Catalan | English |
task1589_scifact_classification |
Classification | Text Quality Evaluation | Scientific Research Papers | English | English |
task1590_diplomacy_text_generation |
Text generation based on diplomacy_detection | Dialogue Generation | Game, Dialogue | English | English |
task1591_allocine_classification |
Classification (based on allocine) | Sentiment Analysis | Reviews -> Movies | French | English |
task1592_yahoo_answers_topics_classfication |
Classification based on yahoo_answers_topics | Text Categorization | Miscellaneous | English | English |
task1593_yahoo_answers_topics_classification |
Classification based on yahoo_answers_topics | Text Categorization | Miscellaneous | English | English |
task1594_yahoo_answers_topics_question_generation |
Question Generation based on yahoo_answers_topics | Question Generation | Miscellaneous | English | English |
task1595_event2mind_text_generation_1 |
Creating text (emotional reaction) based on event2Mind event prompts | Misc. | Stereotypes, Sociology, Commonsense -> Concepts and Relations -> Social Commonsense | English | English |
task1596_event2mind_text_generation_2 |
Creating text (intent) based on event2Mind event prompts | Misc. | Stereotypes, Sociology, Commonsense -> Concepts and Relations -> Social Commonsense | English | English |
task1597_nyc_slot_filling |
Categorizing elements of information from text from the NYC database | Information Extraction | Public Places -> Restaurants | English | English |
task1598_nyc_long_text_generation |
Creating sentences based off of some information from the NYC database | Data to Text | Public Places -> Restaurants, Reviews -> Restaurants | English | English |
task1599_smcalflow_classification |
Classify given utterance into user or agent | Speaker Identification | Commonsense -> Concepts and Relations -> Social Commonsense, Dialogue | English | English |
task1600_smcalflow_sentence_generation |
Given a agents' reply, generate a users' utterance | Dialogue Generation | Commonsense -> Concepts and Relations -> Social Commonsense, Dialogue | English | English |
task1601_webquestions_answer_generation |
Given a question and URL, generate an answer | Question Answering | Knowledge Base -> Freebase | English | English |
task1602_webquestion_question_genreation |
Given an answer and URL, generate a question | Question Generation | Knowledge Base -> Freebase | English | English |
task1603_smcalflow_sentence_generation |
Given a user utterance, generate agents' utterance | Dialogue Generation | Dialogue | English | English |
task1604_ethos_text_classification |
Classifying text to Hate or Not Hate | Toxic Language Detection | Social Media | English | English |
task1605_ethos_text_classification |
Classifying text to Violence or Not Violence | Toxic Language Detection | Social Media | English | English |
task1606_ethos_text_classification |
Classifying if text has Gender Crticism | Toxic Language Detection | Social Media | English | English |
task1607_ethos_text_classification |
Classifying text to Religious Criticism | Toxic Language Detection | Social Media | English | English |
task1608_xquad_en_answer_generation |
Generating answers to xquad en questions | Question Answering | Wikipedia | English | English |
task1609_xquad_en_question_generation |
Generating questions (based on xquad en) | Question Generation | Wikipedia | English | English |
task1610_xquad_es_answer_generation |
Generating answers to xquad es (Spanish) questions | Question Answering | Wikipedia | Spanish | Spanish |
task1611_xquad_es_question_generation |
Generating questions (based on xquad es (Spanish)) | Question Generation | Wikipedia | Spanish | Spanish |
task1612_sick_label_classification |
Classification of labels correctly to show relation between two sentences (based on the sick dataset) | Textual Entailment | Captions -> Video Captions, Captions -> Image Captions | English | English |
task1613_sick_given_category_generate_sentence |
Generate a sentence based that meets the given criteria (based on the sick dataset) | Sentence Composition | Captions -> Video Captions, Captions -> Image Captions | English | English |
task1614_sick_text_modify |
Derive a sentence from the given sentence (based on the sick dataset) | Paraphrasing | Captions -> Video Captions, Captions -> Image Captions | English | English |
task1615_sick_tclassify_b_relation_a |
Classify the correct relation between the second and first sentence (based on the sick dataset) | Textual Entailment | Captions -> Video Captions, Captions -> Image Captions | English | English |
task1616_cc_alligned_translate_eng_tel |
Translate from English to Telugu | Translation | Web | English | Telugu |
task1617_cc_alligned_translate_tel_eng |
Translate from Telugu to English | Translation | Web | Telugu | English |
task1618_cc_alligned_classify_tel_eng |
Classify if a sentence is in Telugu or English Language | Language Identification | Web | Telugu, English | English |
task1619_menyo20k-mt_en_yo_translation |
Given an English sentence convert it to Yoruba. | Translation | News, TED Talks, Captions -> Video Captions, Natural Science | English | Yoruba |
task1620_menyo20k-mt_yo_en_translation |
Given a sentence in Yoruba convert it to English. | Translation | News, TED Talks, Captions -> Video Captions, Natural Science | Yoruba | English |
task1621_menyo20k-mt_en_yo_language_identification |
Given a sentence identify if it is in Yoruba or English. | Language Identification | News, TED Talks, Captions -> Video Captions, Natural Science | Yoruba, English | English |
task1622_disfl_qa_text_modication |
Given a disfluent question, convert it to a proper question. | Question Rewriting | Wikipedia | English | English |
task1623_disfl_qa_disfluent_question_classification |
Given a question, predict whether it is disfluent or proper. | Text Quality Evaluation | Wikipedia | English | English |
task1624_disfl_qa_question_yesno_classification |
Given a context and a question, predict if a question is answerable or not based on the context. | Answerability Classification | Wikipedia | English | English |
task1625_disfl_qa_asnwer_generation |
Given a context and a question, return an answer to the question based on context. | Question Answering | Wikipedia | English | English |
task1626_copa_hr_question_answering |
Given a sentence and 2 labels, select the correct label | Cause Effect Classification | Commonsense -> Concepts and Relations | Croatian | Croatian |
task1627_copa_hr_classification |
Given a question and two label, classify the group in which the choice and the statement are related | Cause Effect Classification | Commonsense -> Concepts and Relations | Croatian | English |
task1628_copa_hr_question_answering |
Given a sentence and four label, select the correct label. | Cause Effect Classification | Commonsense -> Concepts and Relations | Croatian | Croatian |
task1629_copa_hr_classification |
Given two statements, classify the relation between them | Cause Effect Classification | Commonsense -> Concepts and Relations | Croatian | English |
task1630_openpi_classification |
Given a passage as input, print the output as the category to which the passage belongs | Text Categorization | Web | English | English |
task1631_openpi_answer_generation |
Use the given information to generate a grammatically correct sentence as output | Data to Text | Web | English | English |
task1637_doqa2.1_cooking_text_summarization |
Generating title from text (based on DoQA 2.1 cooking data) | Question Generation | Knowledge Base, Food | English | English |
task1638_doqa2.1_movies_text_summarization |
Generating title from text (based on DoQA 2.1 movie data) | Question Generation | Knowledge Base, Movies | English | English |
task1639_doqa2.1_travel_text_summarization |
Generating title from text (based on DoQA 2.1 travel data) | Question Generation | Knowledge Base, Geography | English | English |
task1640_aqa1.0_answerable_unanswerable_question_classification |
Classifying questions (based on AQA 1.0) | Answerability Classification | Wikipedia | English | English |
task1645_medical_question_pair_dataset_text_classification |
Classification of Medical Question Pair Dataset in two categories | Text Matching | Medicine, Healthcare | English | English |
task1646_dataset_card_for_catalonia_independence_corpus_text_classification |
Classification of Catalonia Independence Corpus into three categories | Stance Detection | Medicine, Healthcare | Spanish, Catalan | English |
task1647_opus_books_en-pt_translation |
Translation from English to Portuguese using opus dataset | Translation | Books | English | Portuguese |
task1648_opus_books_en-sv_translation |
Translation from English to Swedish using opus dataset | Translation | Books | English | Swedish |
task1649_opus_books_en-no_translation |
Translation from English to Norwegian using opus dataset | Translation | Books | English | Norwegian |
task1650_opus_books_en-fi_translation |
Translation from English to Finnish using opus dataset | Translation | Books | English | Finnish |
task1651_opus_books_en-es__translation |
Translation from English to Spanish using opus dataset | Translation | Books | English | Spanish |
task1652_opus_books_ca-en_translation |
Translation from Catalan to English using opus dataset | Translation | Books | English | Catalan |
task1654_mkb_translation |
Translation of sentence from English to Hindi | Translation | Captions -> Video Captions, Government and Politics | English | Hindi |
task1655_mkb_translation |
Translation of sentence from Hindi to English | Translation | Captions -> Video Captions, Government and Politics | Hindi | English |
task1656_gooaq_answer_generation |
short_answer generation for given question | Question Answering | Web | English | English |
task1657_gooaq_question_generation |
question generation for a given answer | Question Generation | Web | English | English |
task1658_billsum_summarization |
Generating summary (based on billsum) | Summarization | Government and Politics | English | English |
task1659_title_generation |
Generating Title (based on billsum) | Title Generation | Government and Politics | English | English |
task1660_super_glue_question_generation |
Generating guestions (based on super_glue) | Question Generation | Wikipedia | English | English |
task1661_super_glue_classification |
Classification (based on super_glue) | Question Answering | Wikipedia | English | English |
task1662_cedr_ru_classification |
Generating correct emotion label corresponding to the given Russian text. | Sentiment Analysis | Social Media | Russian | English |
task1663_cedr_ru_incorrect_classification |
Generating incorrect emotion label corresponding to the given Russian text. | Wrong Candidate Generation | Social Media | Russian | English |
task1664_winobias_text_generation |
Identifying coreferences in a given sentence and generating the set of coreference words in the sentence. | Coreference Resolution | Professions, Commonsense | English | English |
task1665_trainglecopa_question_generation |
Generating a Question for the given premise from traingleCOPA dataset | Question Generation | Movies, Narrative | English | English |
task1666_cail2018_answer_generation |
Generating answers (based on cail2018) | Information Extraction | Justice, Jurisprudence, Law | Chinese | Chinese |
task1667_cail2018_answer_generation |
Generating answers (based on cail2018) | Information Extraction | Justice, Jurisprudence, Law | Chinese | Chinese |
task1669_md_gender_bias_text_modification |
Modifying text (based on md gender bias) | Sentence Perturbation | Wikipedia, Dialogue, Miscellaneous | English | English |
task1670_md_gender_bias_text_modification |
Modifying text (based on md gender bias) | Sentence Perturbation | Wikipedia, Dialogue, Miscellaneous | English | English |
task1676_xquad-ca_translation |
Translate questions from Catalan to English in the XQuAD-ca dataset | Translation | Wikipedia | Catalan | English |
task1677_xquad-ca_translation |
Translate questions from English to Catalan in the XQuAD-ca dataset | Translation | Wikipedia | English | Catalan |
task1678_mathqa_answer_selection |
Selecting answers to mathqa questions | Question Answering | Mathematics | English | English |
task1685_menyo20k_translation |
Language translation from English to Yoruba | Translation | News, TED Talks, Captions -> Video Captions, Natural Science | English | Yoruba |
task1686_menyo20k_translation |
Language translation from Yoruba to English | Translation | News, TED Talks, Captions -> Video Captions, Natural Science | Yoruba | English |
task1689_qed_amara_translation |
Language translation from English to French | Translation | Captions -> Video Captions | English | French |
task1690_qed_amara_translation |
Language translation from French to English | Translation | Captions -> Video Captions | French | English |
task1691_qed_amara_translation |
Language translation from English to Spanish | Translation | Captions -> Video Captions | English | Spanish |
task1692_qed_amara_translation |
Language translation from Spanish to English | Translation | Captions -> Video Captions | Spanish | English |
task1703_ljspeech_textmodification |
Digit to Text in ljspeech | Number Conversion | Books | English | English |
task1704_ljspeech_textmodification |
Text to Digit in ljspeech | Number Conversion | Books | English | English |
task1705_ljspeech_classification |
Finding Proper Nouns in ljspeech | Named Entity Recognition | Books | English | English |
task1706_ljspeech_classification |
Correct Punctuation in ljspeech | Punctuation Error Detection | Books | English | English |
task1711_poki_text_generation |
Given a title, generate a short poem that should look like written by a kid. | Poem Generation | Books | English | English |
task1712_poki_classification |
Given a short poem, classify whether is written by an elementary kid or a high school kid. | Text Categorization | Books | English | English |
task1713_convai3_sentence_generation |
Given a user's request, predict what the user is trying to do. | Intent Identification | Dialogue | English | English |
task1714_convai3_sentence_generation |
Given a user's intent and computer response, predict what will the user's response will be. | Dialogue Generation | Dialogue | English | English |
task1720_civil_comments_toxicity_classification |
Classify toxicity | Toxic Language Detection | Dialogue, Social Media | English | English |
task1721_civil_comments_obscenity_classification |
Classify Obscenity | Toxic Language Detection | Dialogue, Social Media | English | English |
task1722_civil_comments_threat_classification |
Classify Threat | Toxic Language Detection | Dialogue, Social Media | English | English |
task1723_civil_comments_sexuallyexplicit_classification |
Classify Sexually Explicit Content | Toxic Language Detection | Dialogue, Social Media | English | English |
task1724_civil_comments_insult_classification |
Classify Insult | Toxic Language Detection | Dialogue, Social Media | English | English |
task1725_civil_comments_severtoxicity_classification |
Classify Severe Toxicity | Toxic Language Detection | Dialogue, Social Media | English | English |
task1726_mathqa_correct_answer_generation |
Generate correct answers for math questions | Question Answering | Mathematics | English | English |
task1727_wiqa_what_is_the_effect |
Find the effect of an event on another event, based on an introduced process | Question Answering | Natural Science | English | English |
task1728_web_nlg_data_to_text |
Generate a textual description of a set of data triples. | Data to Text | Wikipedia | English | English |
task1729_personachat_generate_next |
Generate the next utterance in a conversation | Dialogue Generation | Dialogue | English | English |
task1730_personachat_choose_next |
Choose the next utterance in a conversation from four candidates | Dialogue Generation | Dialogue | English | English |
task1731_quartz_question_answering |
Choose an answer to the given question based on the paragraph | Question Answering | Natural Science | English | English |
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