diff --git a/EL_entity_linking/eval/el_evaluator.py b/EL_entity_linking/eval/el_evaluator.py
index b44ac91..010cedd 100644
--- a/EL_entity_linking/eval/el_evaluator.py
+++ b/EL_entity_linking/eval/el_evaluator.py
@@ -36,6 +36,7 @@ def calculate_f1(precision, recall):
 def evaluate_dbpedia(gold_answers, system_answers):
     count, total_p, total_r, total_f1 = 0, 0, 0, 0
     for ques_id in gold_answers:
+        print(ques_id)
         count += 1
         # if an answer is not provided to a question, we just move on
         if ques_id not in system_answers:
@@ -48,9 +49,11 @@ def evaluate_dbpedia(gold_answers, system_answers):
         # collect all gold entities
         all_gold_ents = set()
         for gold_ent_set in gold_answer_list:
-            all_gold_ents.update(gold_ent_set)
+            all_gold_ents.add(gold_ent_set)
 
         # mark all correct answers from system answers
+        print("gold entities: ",all_gold_ents)
+        print("system entities: ",system_entities)
         for rel in system_entities:
             if rel in all_gold_ents:
                 correct_count += 1
@@ -58,23 +61,25 @@ def evaluate_dbpedia(gold_answers, system_answers):
         # check how many entities sets are covered in system answers. In ground truth, we have multiple correct
         # entities for a given slot.
         # For example, {"dbo:locatedInArea", "dbo:city", "dbo:isPartOf", "dbo:location", "dbo:region"}
-        for gold_ent_set in gold_answer_list:
+        for ent in gold_answer_list:
             gold_ent_count += 1
-            found_ent = False
-            for rel in gold_ent_set:
-                if rel in system_entities:
-                    found_ent = True
-                    system_entities.remove(rel)
-                    break
-            if found_ent:
+            if ent in system_entities:
                 found_count += 1
-
+        print("sys_ent_count: ", sys_ent_count)
+        print("gold_ent_count: ",gold_ent_count)
+        print("correct_count: ", correct_count)
+        print("found_count: ",found_count)
         # precision, recall and F1 calculation
-        precision = correct_count / sys_ent_count
-        recall = found_count / gold_ent_count
+        precision = correct_count / (sys_ent_count+0.0000001)
+        recall = found_count / (gold_ent_count+0.0000001)
         total_p += precision
         total_r += recall
         total_f1 += calculate_f1(precision, recall)
+        print("precision :",precision)
+        print("recall: ",recall)
+        print("f1: ",calculate_f1(precision, recall))
+        print("average f1 so far:",(total_f1/count))
+        print("====================================")
 
     return total_p/count, total_r/count, total_f1/count