Update app.py

app.py

@@ -11,10 +11,14 @@ examples = [
 def ner(text):
     doc = nlp(text)
     final_output = []
+    flagged_categories = ['CARDINAL', 'DATE', 'MONEY', 'PERCENT', 'QUANTITY', 'TIME', 'ORDINAL']
     
     for ent in doc.ents:
-      output = {'entity': ent.label_, 'word': ent.text, 'start': int(ent.start_char), 'end': int(ent.end_char)}
-      final_output.append(output)
+      label = ent.label_
+  
+      if label not in flagged_categories:
+          output = {'entity': ent.label_, 'word': ent.text, 'start': int(ent.start_char), 'end': int(ent.end_char)}
+          final_output.append(output)
         
     return {"text": text, "entities": final_output}