input: from typing import Dict, Any
  import nltk
  from nltk.sentiment import vader
  
  def classify_sentiment(sentence: str) -> str:
      """ Classifies the sentiment of a movie review as either negative or positive
      using the VADER sentiment analysis tool from the Natural Language Toolkit (nltk).
      >>> 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 absolutely wonderful!')
      'The sentiment of the sentence is positive!'
      """
      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!'
output:     if scores['neg'] > scores['pos']:
          return 'The sentiment of the sentence is negative!'
      else:
          return 'The sentiment of the sentence is positive!'