code: def extended_noun_chunks(sentence):
      noun_chunks = {(np.start, np.end) for np in sentence.noun_chunks}
      np_start, cur_np = 0, "NONE"
      for i, token in enumerate(sentence):
          np_type = (
              token.pos_ if token.pos_ in {"NOUN", "PROPN"} else "NONE"
          )
          if np_type != cur_np:
              if cur_np != "NONE":
                  noun_chunks.add((np_start, i))
              if np_type != "NONE":
                  np_start = i
              cur_np = np_type
      if cur_np != "NONE":
          noun_chunks.add((np_start, len(sentence)))
      return [sentence[s:e] for (s, e) in sorted(noun_chunks)]
  
file_path: fairseq/examples/roberta/wsc/wsc_utils.py
imports: import json
  from functools import lru_cache
label_desc: Use image node_id 2 for calling a global function with example usage: extended_noun_chunks(sentence) and returns: unknown