input: from typing import List
  import nltk
  from nltk.sentiment import vader
  
  def classify_sentiment(reviews: List[str]) -> List[str]:
      """Classify the sentiment of a list of movie reviews using Natural Language Processing (NLP).
      The sentiment is determined based on the polarity scores provided by the VADER sentiment analyzer.
      >>> classify_sentiment(['The movie was terrible. It felt like it would never end!'])
      ['The sentiment of the sentence is negative!']
      """
      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:     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