docs: def _annotate_bifurcated_extend_data(self, row, smaller, larger, tokenize,
                                           join):
          """Returns `row` annotated with whether it should be deleted or not.
  
          An n-gram is marked for deletion if:
  
          * its label count is 1 and its constituent (n-1)-grams also
            have a label count of 1; or
  
          * there is a containing (n+1)-gram that has the same label
            count.
  
          :param row: row of witness n-grams to annotate
          :type row: `pandas.Series`
          :param smaller: rows of (n-1)-grams for this witness
          :type smaller: `pandas.DataFrame`
          :param larger: rows of (n+1)-grams for this witness
          :type larger: `pandas.DataFrame`
          :param tokenize: function to tokenize an n-gram
          :param join: function to join tokens
          :rtype: `pandas.Series`
  
          """
          lcf = constants.LABEL_COUNT_FIELDNAME
          nf = constants.NGRAM_FIELDNAME
          ngram = row[constants.NGRAM_FIELDNAME]
          label_count = row[constants.LABEL_COUNT_FIELDNAME]
          if label_count == 1 and not smaller.empty:
              # Keep a result with a label count of 1 if its
              # constituents do not also have a count of 1.
              ngram_tokens = tokenize(ngram)
              sub_ngram1 = join(ngram_tokens[:-1])
              sub_ngram2 = join(ngram_tokens[1:])
              pattern = FilteredWitnessText.get_filter_ngrams_pattern(
                  [sub_ngram1, sub_ngram2])
              if smaller[smaller[constants.NGRAM_FIELDNAME].str.match(pattern)][
                      constants.LABEL_COUNT_FIELDNAME].max() == 1:
                  row[DELETE_FIELDNAME] = True
          elif not larger.empty and larger[larger[nf].str.contains(
                  ngram, regex=False)][lcf].max() == label_count:
              # Remove a result if the label count of a containing
              # n-gram is equal to its label count.
              row[DELETE_FIELDNAME] = True
          return row