input: Write a python function to analyze the sentiment of a given sentence using nltk's SentimentIntensityAnalyzer.
  assert analyze_sentiment("The food was really bad.") == 'negative'
  assert analyze_sentiment("I love this place!") == 'positive'
  assert analyze_sentiment("It was an average experience.") == 'neutral'
output: def analyze_sentiment(sentence):
      from nltk.sentiment.vader import SentimentIntensityAnalyzer
      from nltk import download
      download('vader_lexicon')
      
      sia = SentimentIntensityAnalyzer()
      score = sia.polarity_scores(sentence)
      
      if score['compound'] >= 0.05:
          return 'positive'
      elif score['compound'] <= -0.05:
          return 'negative'
      else:
          return 'neutral'