input: 
  def classify_text_sentiment(text: str, classifier: NaiveBayesClassifier) -> str:
      """ Classify the given text document into a sentiment class, either 'positive' or 'negative'.
      >>> classify_text_sentiment("This is a great movie!", classifier)
      'positive'
      >>> classify_text_sentiment("This movie was terrible", classifier)
      'negative'
      """
      return classifier.classify(label_words(nltk.word_tokenize(text)))
  
output:     return classifier.classify(nltk.word_tokenize(text))