code: def sentence_similarity(sentence1, sentence2):
      
      # Tokenize and tag
      sentence1 = pos_tag(word_tokenize(sentence1))
      sentence2 = pos_tag(word_tokenize(sentence2))
  
      # Get the synsets for the tagged words
      synsets1 = [tagged_to_synset(*tagged_word) for tagged_word in sentence1]
      synsets2 = [tagged_to_synset(*tagged_word) for tagged_word in sentence2]
  
      # Filter out the Nones
      synsets1 = [ss for ss in synsets1 if ss]
      synsets2 = [ss for ss in synsets2 if ss]
      #print(synsets1)
      #print(synsets2)
      score, count = 0.0, 0.0
  
      # For each word in the first sentence
      for synset in synsets1:
          # Get the similarity value of the most similar word in the other sentence
  
          best_score=[synset.path_similarity(ss) for ss in synsets2 if synset.path_similarity(ss)]
  
          # Check that the similarity could have been computed
          if best_score:
              score += max(best_score)
              count += 1
  
      # Average the values
      if count > 0:
          score /= count
      else:
          score = 0
  
      return score
docs: compute the sentence similarity using Wordnet