code: def _get_entailed_hypothesis(tokens, index, number):
      """
      return a sentence that have the entailment semantic with the original sample
      :param tokens: the text
      :param index: the position for the number word
      :param number: number word (int)
      :return: The sentence changed the number word
      """
  
      number = str(number)
      new_digit = np.random.randint(1, 9)
      old_digit = int(number[0])
      while new_digit == old_digit:
          new_digit = np.random.randint(1, 9)
      new_num = str(new_digit) + number[1:]
      new_tokens = []
      if old_digit < new_digit:
          new_tokens = (
              tokens[:index]
              + ["less than", new_num]
              + tokens[index + 1 :]
          )
      else:
          new_tokens = (
              tokens[:index]
              + ["more than", new_num]
              + tokens[index + 1 :]
          )
      return " ".join(new_tokens)
  
label_desc: Use image node_id 1 for calling a global function with example usage: _get_entailed_hypothesis(tokens, index, number) and returns: str