class_docstr: Transforms an input by replacing its words with antonyms provided by
  WordNet. Download nltk_data before running.
  
  Implement follow by Stress Test Evaluation for Natural Language Inference
  For the correctness of trasformation we swap the word has
  best_sense(Wordnet) to its antonym
  
  https://www.aclweb.org/anthology/C18-1198/
  
  Example::
  
      {
          sentence1: I hate this book.
          sentence2: This book is my favorite.
          y: 0
      }
docstr: :param string language: language of transformation
code: def __init__(self, language="eng"):
      r"""
      :param string language: language of transformation
      """
  
      super().__init__()
      self.language = language
      self.blacklist_words = BLACK_LIST_WORD
  
file_path: textflint/textflint/generation/transformation/SM/swap_word.py
imports: from nltk.wsd import lesk
  from ...transformation import Transformation
  from ....common.settings import BLACK_LIST_WORD
label_desc: Use image node_id 1 to create a new SwapWord object from inherited base classes: Transformation with example: obj = SwapWord(language)