input: 
  def classify_sentiment(sentence: str) -> str:
      """Classify the sentiment of a movie review using VADER Sentiment Analysis.
  
      >>> classify_sentiment('The movie was terrible. It felt like it would never end!')
      'The sentiment of the sentence is negative!'
      
      >>> classify_sentiment('I had an amazing time watching this masterpiece.')
      'The sentiment of the sentence is positive!'
      """
      from nltk.sentiment import SentimentIntensityAnalyzer
  
      sid = 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:     
      if scores['neg'] == scores['pos']:
          return 'The sentiment of the sentence is neutral!'
  