code: def get_col_ngrams(
      mention, attrib="words", n_min=1, n_max=1, spread=[0, 0], lower=True
  ):
      
      spans = _to_spans(mention)
      for span in spans:
          for ngram in _get_axis_ngrams(
              span,
              axis="col",
              attrib=attrib,
              n_min=n_min,
              n_max=n_max,
              spread=spread,
              lower=lower,
          ):
              yield ngram
docs: Get the ngrams from all Cells that are in the same column as the given Mention.
  
      Note that if a candidate is passed in, all of its Mentions will be searched.
  
      :param mention: The Mention whose column Cells are 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 spread: The number of cols left and right to also consider "aligned".
      :param lower: If True, all ngrams will be returned in lower case
      :rtype: a *generator* of ngrams