input: def classify_movie_review_sentiment(sentence: str) -> str:
      """ Classify the sentiment of a movie review using Natural Language Processing.
      Example:
      >>> classify_movie_review_sentiment('The movie was terrible. It felt like it would never end!')
      'The sentiment of the sentence is negative!'
      """
      import nltk
      from nltk.sentiment import vader
  
      sid = vader.SentimentIntensityAnalyzer()
      scores = sid.polarity_scores(sentence)
  
      if scores['neg'] > scores['pos']:
          return 'The sentiment of the sentence is negative!'
      else:
          return 'The sentiment of the sentence is positive!'
output:     import nltk
      from nltk.sentiment import vader
  
      sid = vader.SentimentIntensityAnalyzer()
      scores = sid.polarity_scores(sentence)
  
      if scores['neg'] > scores['pos']:
          return 'The sentiment of the sentence is negative!'
      else:
          return 'The sentiment of the sentence is positive!'