input: from typing import List
  
  def classify_sentiment(reviews: List[str]) -> List[str]:
      """ Classify the sentiment of given movie reviews using Natural Language Processing.
      >>> classify_sentiment(['The movie was terrible. It felt like it would never end!'])
      ['negative']
      >>> classify_sentiment(['The movie was amazing and exceeded all expectations!'])
      ['positive']
      """
      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('negative')
          else:
              sentiments.append('positive')
      
      return sentiments
output:     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('negative')
          else:
              sentiments.append('positive')
      
      return sentiments