docstr: Return a string of text containing part-of-speech, lemma pairs.
code: def get_text_index_string(self, text):
      """
      Return a string of text containing part-of-speech, lemma pairs.
      """
      bigram_pairs = []
  
      if len(text) <= 2:
          text_without_punctuation = text.translate(
              self.punctuation_table
          )
          if len(text_without_punctuation) >= 1:
              text = text_without_punctuation
  
      document = self.nlp(text)
  
      if len(text) <= 2:
          bigram_pairs = [token.lemma_.lower() for token in document]
      else:
          tokens = [
              token
              for token in document
              if token.is_alpha and not token.is_stop
          ]
  
          if len(tokens) < 2:
              tokens = [token for token in document if token.is_alpha]
  
          for index in range(1, len(tokens)):
              bigram_pairs.append(
                  "{}:{}".format(
                      tokens[index - 1].pos_,
                      tokens[index].lemma_.lower(),
                  )
              )
  
      if not bigram_pairs:
          bigram_pairs = [token.lemma_.lower() for token in document]
  
      return " ".join(bigram_pairs)
  
file_path: ChatterBot/chatterbot/tagging.py
imports: import string
  from chatterbot import languages
label_desc: Use image node_id 2 for calling the PosLemmaTagger obj's underlying member method code with example usage: obj.get_text_index_string(text) and returns: str