Key topics
- Information extraction
- Named entity recognition
Objective
We want build a system that can tag our tweets with entities that are useful to us. For example, we may want to tag a tweet with the entity "N Line" or "4th and King." This helps us know exactly which transit-related entities are being talked about.
First steps
There are two approaches for this task. One is a supervised approach, where we determine a set of entities that are interesting to us and tag tweets either by keyword matching or using a classifier. The other is an unsupervised approach, which is called named entity recognition. Here, we try to automatically extract named entities from a dataset.
Useful tools
Classification - scikit-learn
Named entity recognition spacy
Key topics
Objective
We want build a system that can tag our tweets with entities that are useful to us. For example, we may want to tag a tweet with the entity "N Line" or "4th and King." This helps us know exactly which transit-related entities are being talked about.
First steps
There are two approaches for this task. One is a supervised approach, where we determine a set of entities that are interesting to us and tag tweets either by keyword matching or using a classifier. The other is an unsupervised approach, which is called named entity recognition. Here, we try to automatically extract named entities from a dataset.
Useful tools
Classification - scikit-learn
Named entity recognition spacy