input: 
  def text_classification(text: str, classifier) -> str:
      """ Classify a given text into 'positive' or 'negative' using a trained NaiveBayesClassifier.
      >>> text_classification("This movie was ok", classifier)
      'negative'
      >>> text_classification("This is a great movie!", classifier)
      'positive'
      """
      words = nltk.word_tokenize(text)
      return classifier.classify(label_words(words))
  
output:     words = nltk.word_tokenize(text)
      return classifier.classify(label_words(words))