code: def _get_chunk_ratings(self, sentence, significant_stems):
      chunks = []
      NONSIGNIFICANT_CHUNK = [0] * self.max_gap_size
  
      in_chunk = False
      for order, word in enumerate(sentence.words):
          stem = self.stem_word(word)
          # new chunk
          if stem in significant_stems and not in_chunk:
              in_chunk = True
              chunks.append([1])
          # append word to chunk
          elif in_chunk:
              is_significant_word = int(stem in significant_stems)
              chunks[-1].append(is_significant_word)
  
          # end of chunk
          if (
              chunks
              and chunks[-1][-self.max_gap_size :]
              == NONSIGNIFICANT_CHUNK
          ):
              in_chunk = False
  
      return tuple(map(self._get_chunk_rating, chunks))
  
file_path: sumy/sumy/summarizers/luhn.py
imports: from __future__ import absolute_import
  from __future__ import division, print_function, unicode_literals
  from ..models import TfDocumentModel
  from ._summarizer import AbstractSummarizer
label_desc: Use image node_id 6 for calling the LuhnSummarizer obj's underlying member method code with example usage: obj._get_chunk_ratings(sentence, significant_stems) and returns: tuple