class_docstr: This class is used to extract nouns, proper nouns, phrases from text, including descriptions and
  url links
class_docstr_tok: ["This","class","is","used","to","extract","nouns",",","proper","nouns",",","phrases","from","text",",","including","descriptions","and","url","links"]
code: def extract_words(
      self,
      text,
      good_tags=set(["NN", "NNS", "NNP", "VBP", "VBZ", "VBG", "VBN"]),
  ):
      pos_tags = self._tagger(self._word_tokenize(text))
      words = [
          word
          for word, tag in pos_tags
          if tag in good_tags
          and not all(char in self._punct for char in word)
      ]
      return word_process(words)
  
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 4 for calling the Extraction obj's underlying member method code with example usage: obj.extract_words(text, good_tags) and returns: word_process