input: Write a function to classify the sentiment of movie reviews using Natural Language Processing. The function should analyze the sentiment of the given sentence and determine if it is negative or positive. If the negative score is higher than the positive score, the function should return "The sentiment of the sentence is negative!". Otherwise, it should return "The sentiment of the sentence is positive!".
  
  import nltk
  from nltk.sentiment import vader
  
  def classify_movie_review(sentence):
      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!'
  
  assert classify_movie_review('The movie was terrible. It felt like it would never end!') == 'The sentiment of the sentence is negative!'
  assert classify_movie_review('The movie was fantastic. It felt like it ended too soon!') == 'The sentiment of the sentence is positive!'
output: def classify_movie_review(sentence):
      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!'