input: from typing import List
  
  def classify_sentiment(reviews: List[str]) -> List[str]:
      """ Classify the sentiment of a list of movie reviews using Natural Language Processing.
      >>> 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 amazing. I loved every bit of it!'])
      ['The sentiment of the sentence is positive!']
      """
      from nltk.sentiment import vader
      sid = vader.SentimentIntensityAnalyzer()
      results = []
      
      for review in reviews:
          scores = sid.polarity_scores(review)
          if scores['neg'] > scores['pos']:
              results.append('The sentiment of the sentence is negative!')
          else:
              results.append('The sentiment of the sentence is positive!')
      
      return results
output:     from nltk.sentiment import vader
      sid = vader.SentimentIntensityAnalyzer()
      results = []
      
      for review in reviews:
          scores = sid.polarity_scores(review)
          if scores['neg'] > scores['pos']:
              results.append('The sentiment of the sentence is negative!')
          else:
              results.append('The sentiment of the sentence is positive!')
      
      return results