class_docstr: Transforms the polarity of 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: "BAD spicy tuna roll, great asian salad."
docstr: Transform the conjunction words in sentence.
  
  :param str term_id: term id
  :param list trans_words: tokenized words of transformed sentence
  :param str trans_polarity: transformed polarity
  :return list: tokenized words of transformed sentence
code: def _trans_conjunction(self, term_id, trans_words, trans_polarity):
      r"""
      Transform the conjunction words in sentence.
  
      :param str term_id: term id
      :param list trans_words: tokenized words of transformed sentence
      :param str trans_polarity: transformed polarity
      :return list: tokenized words of transformed sentence
  
      """
      term_list = self.term_list
      aspect_opinions = set()
      conjunction_list = ["and", "but"]
      aspect_opinions.add(
          aspect_opi
          for aspect_opi in term_list[term_id]["opinion_words"]
      )
      other_opinions, other_polarity = self.get_other_opinions(
          term_list, term_id
      )
  
      if (
          len(other_polarity) > 0
          and len(aspect_opinions & other_opinions) == 0
      ):
          conjunction_idx = self.get_conjunction_idx(
              trans_words, term_list[term_id], conjunction_list
          )
          if (
              conjunction_idx is not None
              and trans_polarity not in other_polarity
          ):
              trans_words[conjunction_idx] = "but"
          elif (
              conjunction_idx is not None
              and trans_polarity in other_polarity
          ):
              trans_words[conjunction_idx] = "and"
  
      return trans_words
  
file_path: textflint/textflint/generation/transformation/ABSA/rev_tgt.py
imports: from copy import deepcopy
  from .absa_transformation import ABSATransformation
label_desc: Use image node_id 5 for calling the RevTgt obj's underlying member method code with example usage: obj._trans_conjunction(term_id, trans_words, trans_polarity) and returns: trans_words