fix result visualization

app.py

@@ -28,4 +28,4 @@ else:
     tokens = baseline_classifier(txt)
 
 st.subheader("Entity analysis:")
-annotated_text(annotate_sentence(sentence, tokens))
+annotated_text(annotate_sentence(txt, tokens))

helpers.py

@@ -11,7 +11,6 @@ augmented_classifier = pipeline("ner",
 
 def annotate_sentence(sentence, predictions):
     colors = {
-        'null': '#bfbfbf',  # Pastel gray
         'GeneOrGeneProduct': '#aad4aa',  # Pastel green
         'DiseaseOrPhenotypicFeature': '#f8b400',  # Pastel orange
         'ChemicalEntity': '#a4c2f4',  # Pastel blue
@@ -24,7 +23,11 @@ def annotate_sentence(sentence, predictions):
     for p in predictions:
         if sentence[i:p['start']] != '':
             output.append(sentence[i:p['start']])
-        output.append((p['word'], p['entity_group'], colors[p['entity_group']]))
+        output.append(
+            (sentence[p['start']:p['end']], p['entity_group'], colors[p['entity_group']])
+            if p['entity_group'] != 'null'
+            else sentence[p['start']:p['end']]
+            )
         i = p['end']
     if sentence[p['end']:]:
         output.append(sentence[p['end']:])