docs: def extract_features(self, phrase):
          """
          This function will extract features from the phrase being used. 
          Currently, the feature we are extracting are unigrams of the text corpus.
          """
          
          words = nltk.word_tokenize(phrase)
          features = {}
          for word in words:
              features['contains(%s)' % word] = (word in words)
          return features