Update app.py

app.py

@@ -194,7 +194,7 @@ def _inference_ner_spancat(text, limit_outputs=10):
     for doc in nlp.pipe(text):
         spans = doc.spans["sc"]
         #comp_raw_text = dict( sorted( dict(zip([str(x) for x in spans],[float(x)*penalty for x in spans.attrs['scores']])).items(), key=lambda x: x[1], reverse=True) )
-        company_list = list(set([str(span).replace('\'s', '').replace('’s','') for span in filter_spans(spans, keep_longest=True)]))[:limit_outputs]
+        company_list = list(set([str(span).replace('\'s', '').replace('\u2019s','') for span in filter_spans(spans, keep_longest=True)]))[:limit_outputs]
         out.append(get_company_sectors(company_list))
     return out