code: def word_tokenize(text):
      trans = str.maketrans(dict.fromkeys(string.punctuation))
      res = text.translate(trans)
      tokens = reg_tokenizer.tokenize(res)
      return list(
          filter(
              lambda token: word_pattern.match(token)
              and len(token) >= 1,
              tokens,
          )
      )
  
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 1 for calling a global function with example usage: word_tokenize(text) and returns: list