input: from typing import List
  
  def classify_sentiment(reviews: List[str]) -> List[str]:
      """ Classify the sentiment of movie reviews using Natural Language Processing (NLP).
      >>> classify_sentiment(['The movie was terrible. It felt like it would never end!'])
      ['The sentiment of the sentence is negative!']
      >>> classify_sentiment(['This was an amazing film! I loved every second of it.'])
      ['The sentiment of the sentence is positive!']
      """
      import nltk
      from nltk.sentiment import vader
  
      sid = vader.SentimentIntensityAnalyzer()
      sentiments = []
  
      for review in reviews:
          scores = sid.polarity_scores(review)
          if scores['neg'] > scores['pos']:
              sentiments.append('The sentiment of the sentence is negative!')
          else:
              sentiments.append('The sentiment of the sentence is positive!')
      
      return sentiments
output:     import nltk
      from nltk.sentiment import vader
  
      sid = vader.SentimentIntensityAnalyzer()
      sentiments = []
  
      for review in reviews:
          scores = sid.polarity_scores(review)
          if scores['neg'] > scores['pos']:
              sentiments.append('The sentiment of the sentence is negative!')
          else:
              sentiments.append('The sentiment of the sentence is positive!')
      
      return sentiments