Update app.py

app.py

@@ -45,6 +45,32 @@ with st.sidebar:
   misc = st.checkbox("MISC")
   if misc:
     st.write("Miscellaneous")
+
+  with st.expander("entity_group"):
+    st.write('''
+        This is the tag that has been assigned to an entity.
+    ''')
+
+  with st.expander("score"):
+    st.write('''
+        This indicates the confidence level that a tag has been assigned to an entity.
+    ''')
+
+   with st.expander("word"):
+    st.write('''
+        This is the entity that has been extracted from your text data.
+    ''')
+
+   with st.expander("start-end"):
+    st.write('''
+        This indicates the postiion of the entity in your text data.
+    ''')
+    
+  with st.expander("Limitations and Bias"):
+    st.write('''
+        The Named Entity Recognition (NER) model used in this demo app is limited by its training dataset of entity-annotated news articles from a specific span of time. This means that it might not perform excellent for all use cases in different domains. Furthermore, the model may occassionally split words into different parts.
+    ''')
+