code: def create_statement_inspection_table(sts: List[Influence]):
      
  
      columns = [
          "un_groundings",
          "subj_polarity",
          "obj_polarity",
          "Sentence",
          "Source API",
      ]
  
      polarity_to_str = lambda x: "+" if x == 1 else "-" if x == -1 else "None"
      l = []
      for s in sts:
          subj_un_grounding = s.subj.db_refs["UN"][0][0].split("/")[-1]
          obj_un_grounding = s.obj.db_refs["UN"][0][0].split("/")[-1]
          subj_polarity = s.subj_delta["polarity"]
          obj_polarity = s.obj_delta["polarity"]
          subj_adjectives = s.subj_delta["adjectives"]
          for e in s.evidence:
              l.append(
                  (
                      (subj_un_grounding, obj_un_grounding),
                      subj_polarity,
                      obj_polarity,
                      e.text,
                      e.source_api,
                  )
              )
  
      df = pd.DataFrame(l, columns=columns)
      df = df.pivot_table(index=["un_groundings", "Source API", "Sentence"])
  
      def hover(hover_color="#ffff99"):
          return dict(
              selector="tr:hover",
              props=[("background-color", "%s" % hover_color)],
          )
  
      styles = [
          hover(),
          dict(props=[("font-size", "100%"), ("font-family", "Gill Sans")]),
      ]
  
      return df.style.set_table_styles(styles)
docs: Display an HTML representation of a table with INDRA statements to
      manually inspect for validity.
  
      Args:
          sts: A list of INDRA statements to be manually inspected for validity.