code: def lemmatize(self):
          
          _lemmatizer = PatternParserLemmatizer(tokenizer=NLTKPunktTokenizer())
          # WordList object --> Sentence.string
          # add a period (improves parser accuracy)
          _raw = " ".join(self) + "."
          _lemmas = _lemmatizer.lemmatize(_raw)
          return self.__class__([Word(l, t) for l, t in _lemmas])
docs: Return the lemma of each word in this WordList.
  
          Currently using NLTKPunktTokenizer() for all lemmatization
          tasks. This might cause slightly different tokenization results
          compared to the TextBlob.words property.