code: def extract_verbs(self, pos_tags):
      verbs = self.extract_words(pos_tags, set(["VERB"]))
  
      def words_process():
          words, tag = zip(*verbs)
          words = map(lambda x: x.lower(), words)
  
          words = [self._lemma(w, pos="v") for w in words]
          return list(set(words))
  
      return words_process() if verbs else []
  
imports: from sematch.utility import FileIO
  from nltk.stem import WordNetLemmatizer
  from nltk.corpus import wordnet
  import nltk
  from collections import Counter
  import itertools
  import string
  import re
label_desc: Use image node_id 5 for calling the FeatureExtractor obj's underlying member method code with example usage: obj.extract_verbs(pos_tags) and returns: unknown, list