class_docstr: Transforms the polarity of non-target by replacing its opinion words
      with antonyms provided by WordNet or adding the negation that
      pre-defined in our negative word list.
  
  Example::
  
      Original sentence: "BEST spicy tuna roll, great asian salad.
      （Target: spicy tuna roll)"
      Transformed sentence: "BEST spicy tuna roll, not great asian salad."
docstr: Transform the conjunction words in sentence.
  
  :param dict aspect_term: aspect term
  :param list trans_words: tokenized words and terms of
      transformed sentence
  :return list: tokenized words and terms of transformed sentence
code: def _trans_conjunction(self, aspect_term, trans_words):
      r"""
      Transform the conjunction words in sentence.
  
      :param dict aspect_term: aspect term
      :param list trans_words: tokenized words and terms of
          transformed sentence
      :return list: tokenized words and terms of transformed sentence
  
      """
      conjunction_list = ["and"]
      conjunction_idx = self.get_conjunction_idx(
          trans_words, aspect_term, conjunction_list
      )
      if conjunction_idx is not None:
          trans_words[conjunction_idx] = "but"
      return trans_words
  
file_path: textflint/textflint/generation/transformation/ABSA/rev_non.py
imports: from copy import deepcopy
  from ...transformation.ABSA.absa_transformation import ABSATransformation
label_desc: Use image node_id 6 for calling the RevNon obj's underlying member method code with example usage: obj._trans_conjunction(aspect_term, trans_words) and returns: trans_words