code: def convert_string_to_list_of_words(string_list_of_words):
      """
      convert string to list of words
  
      Args:
          string_list_of_words(str): input sentence
  
      Returns:
          list(str): vector of words
  
      """
      string_list_of_words = re.sub(
          r"[-+.^:,\[\]()]", "", str(string_list_of_words)
      )
      tokens = nltk.word_tokenize(string_list_of_words)
  
      words_vec = []
      cntr = 0
      for word in tokens:
          words_vec.insert(cntr, word)
          cntr += 1
  
      return words_vec
  
file_path: nlp-architect/examples/most_common_word_sense/feature_extraction.py
imports: import re
  import nltk
  import numpy
  from numpy import dot
  from numpy.linalg import norm
  from nlp_architect.utils.generic import license_prompt
label_desc: Use image node_id 3 for calling a global function with example usage: convert_string_to_list_of_words(string_list_of_words) and returns: words_vec