code: def get_cell_ngrams(mention, attrib="words", n_min=1, n_max=1, lower=True):
      
      spans = _to_spans(mention)
      for span in spans:
          for ngram in get_sentence_ngrams(
              span, attrib=attrib, n_min=n_min, n_max=n_max, lower=lower
          ):
              yield ngram
          if span.sentence.is_tabular():
              for ngram in chain.from_iterable(
                  [
                      tokens_to_ngrams(
                          getattr(sentence, attrib), n_min=n_min, n_max=n_max, lower=lower
                      )
                      for sentence in _get_table_cells(span.sentence.table)[
                          span.sentence.cell
                      ]
                      if sentence != span.sentence
                  ]
              ):
                  yield ngram
docs: Get the ngrams that are in the Cell of the given mention, not including itself.
  
      Note that if a candidate is passed in, all of its Mentions will be searched.
  
      :param mention: The Mention whose Cell is being searched
      :param attrib: The token attribute type (e.g. words, lemmas, poses)
      :param n_min: The minimum n of the ngrams that should be returned
      :param n_max: The maximum n of the ngrams that should be returned
      :param lower: If True, all ngrams will be returned in lower case
      :rtype: a *generator* of ngrams