get only score at least 0.8

app.py

@@ -39,15 +39,23 @@ def predict(sentence):
     
     # Get the prediction of ner from the model
     result_ner = ner_task(sentence)
-    formatted_ner = f"Number of predicted entities: {len(result_ner)}\n\n"
+    formatted_ner = ""
+    entities_count = 0
     # Print individual entities.
     # Start the count from 1 for intuitive reading.
     for i, result in enumerate(result_ner):
-        formatted_ner +=   f"Number: {i+1} \n" \
-                         + f"Entity: {result['entity_group']}\n" \
-                         + f"Word group: {result['word']}\n" \
-                         + f"Score: {result['score']}\n"
-        formatted_ner += f"{result}\n\n"
+        # Only get the result where score is at least 0.8
+        if result['score'] < 0.8:
+            continue;
+        else:
+            entities_count += 1
+            formatted_ner +=  f"Number: {entities_count} \n" \
+                            + f"Entity: {result['entity_group']}\n" \
+                            + f"Word group: {result['word']}\n" \
+                            + f"Score: {result['score']}\n"
+            formatted_ner += f"{result}\n\n"
+
+    formatted_ner += f"Number of predicted entities: {entities_count}\n\n"
     
     return token_pieces, formatted_ner