Update app.py

app.py

@@ -151,7 +151,9 @@ def genEntities(ann, entity):
                              ent = list(trans_df[trans_df['Class']==entity]['Entity'].unique())
                              entlist = ",".join(ent)
                              st.markdown(f'<p style="background-color:{ent_col[entity]};color:#080808;font-size:16px;">{entlist}</p>', unsafe_allow_html=True)
-                                                                       
+
+
+##======================== Start of NER Tagging ========================
 #lemmatizing the notes to capture all forms of negation(e.g., deny: denies, denying)
 def lemmatize(note, nlp):
     doc = nlp(note)
@@ -224,7 +226,7 @@ def dedupe(items):
             yield item
             seen.add(item)
 
-lem_clinical_note= lemmatize(text, nlp0)
+lem_clinical_note= lemmatize(runtext, nlp0)
 #creating a doc object using BC5CDR model
 doc = nlp1(lem_clinical_note)
 options = get_entity_options()
@@ -240,7 +242,8 @@ doc0 = overwrite_ent_lbl(matcher,doc)
 #visualizing identified Named Entities in clinical input text 
 displacy.render(doc0, style='ent', options=options)
 
-##=== end of NER tagger===
+##======================== End of NER Tagging ========================
+
 def visualize (run_text,output):
     text =''
     splitruntext = [x for x in runtext.split('.')]