code: def filter_and_process_statements(
      sts,
      grounding_score_cutoff: float = 0.8,
      belief_score_cutoff: float = 0.85,
      concepts_of_interest: List[str] = [],
  ):
  
      
      filtered_sts = []
      counters = {}
  
      def update_counter(counter_name):
          if counter_name in counters:
              counters[counter_name] += 1
          else:
              counters[counter_name] = 1
  
      for s in tqdm(sts):
  
          update_counter("Original number of statements")
  
          # Apply belief score threshold cutoff
  
          if not s.belief > belief_score_cutoff:
              continue
          update_counter(f"Statements with belief score > {belief_score_cutoff}")
  
          # Select statements with UN groundings
  
          if s.subj.db_refs.get("UN") is None or s.obj.db_refs.get("UN") is None:
              continue
          update_counter("Statements with UN groundings")
  
          # Apply grounding score cutoffs
  
          if not all(
              x[1] > grounding_score_cutoff
              for x in (y.db_refs["UN"][0] for y in (s.subj, s.obj))
          ):
              continue
          update_counter(
              f"Statements with subj and obj grounding scores > {grounding_score_cutoff}"
          )
  
          # Assign default polarities
  
          if s.subj_delta["polarity"] is None:
              s.subj_delta["polarity"] = 1
          if s.obj_delta["polarity"] is None:
              s.obj_delta["polarity"] = 1
  
          filtered_sts.append(s)
  
      for k, v in counters.items():
          print(f"{k}: {v}")
  
      return filtered_sts
docs: Filter preassembled statements according to certain rules.