input: def classify_sentiment(review: str) -> str:
      """ Classify the sentiment of a given movie review using Natural Language
      Processing. The function will use the VADER sentiment analysis tool from NLTK to 
      determine if the sentiment is positive or negative.
      >>> classify_sentiment('The movie was terrible. It felt like it would never end!')
      'The sentiment of the sentence is negative!'
      >>> classify_sentiment('This movie was a masterpiece of modern cinematic art.')
      'The sentiment of the sentence is positive!'
      """
      import nltk
      from nltk.sentiment import vader
  
      sid = vader.SentimentIntensityAnalyzer()
      scores = sid.polarity_scores(review)
  
      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(review)
  
      if scores['neg'] > scores['pos']:
          return 'The sentiment of the sentence is negative!'
      else:
          return 'The sentiment of the sentence is positive!'