Update app.py

app.py

@@ -325,9 +325,10 @@ if len(match_df) > 0:
 
                         instances = instances[instances.apply(lambda x: x.source_wikidata in [source_wikidata, target_wikidata] and x.target_wikidata in [source_wikidata, target_wikidata], axis=1)]
 
-                        st.write(f"**Total Number of Evidence Instances:** {int(rel_data['n_evidence'])}")
-                        st.write(f"**Number of Instances that support the relation:** {int(rel_data['n_support'])}")
-                        st.write(f"**Average Evidence Score:** {rel_data['avg_score']}")
+                        st.write(f"**Total Number of Inference Instances:** {int(rel_data['n_evidence'])}")
+                        st.write(f"**Number of Instances that support the most frequent relation:** {int(rel_data['n_support'])}")
+                        st.write(f"**Support Ratio:** {rel_data['support_ratio']}")
+                        st.write(f"**Average Inference Score:** {rel_data['avg_score']}")
 
                         st.write("Inferences supporting the relation")
                         instances[['source_en', 'relation', 'target_en', 'text', 'source_wikidata', 'target_wikidata', 'source', 'page_title', 'score', 'section']]
@@ -338,7 +339,7 @@ if len(match_df) > 0:
                         count_dict = dict(Counter(instances.relation.to_list() + neg_instances.relation.to_list()))
                         count_df = pd.DataFrame.from_dict(count_dict, orient='index')
                         count_df.columns = ['count']
-                        st.write("Evidence relation distribution for above edge")
+                        st.write("Inference distribution for above edge")
                         count_df
 
                 st.write("**Conclusion:**")