code: def process_article(
      args,
      tokenizer_func=tokenize,
      token_min_len=TOKEN_MIN_LEN,
      token_max_len=TOKEN_MAX_LEN,
      lower=True,
  ):
      """Parse a Wikipedia article, extract all tokens.
  
      Notes
      -----
      Set `tokenizer_func` (defaults is :func:`~gensim.corpora.wikicorpus.tokenize`) parameter for languages
      like Japanese or Thai to perform better tokenization.
      The `tokenizer_func` needs to take 4 parameters: (text: str, token_min_len: int, token_max_len: int, lower: bool).
  
      Parameters
      ----------
      args : (str, str, int)
          Article text, article title, page identificator.
      tokenizer_func : function
          Function for tokenization (defaults is :func:`~gensim.corpora.wikicorpus.tokenize`).
          Needs to have interface:
          tokenizer_func(text: str, token_min_len: int, token_max_len: int, lower: bool) -> list of str.
      token_min_len : int
          Minimal token length.
      token_max_len : int
          Maximal token length.
      lower : bool
           Convert article text to lower case?
  
      Returns
      -------
      (list of str, str, int)
          List of tokens from article, title and page id.
  
      """
      text, title, pageid = args
      text = filter_wiki(text)
      result = tokenizer_func(text, token_min_len, token_max_len, lower)
      return result, title, pageid
  
imports: import bz2
  import logging
  import multiprocessing
  import re
  import signal
  from pickle import PicklingError
  from xml.etree.ElementTree import iterparse
  from gensim import utils
  from gensim.corpora.dictionary import Dictionary
  from gensim.corpora.textcorpus import TextCorpus
label_desc: Use image node_id 10 for calling a global function with example usage: process_article(args, tokenizer_func, token_min_len, token_max_len, lower) and returns: result,  title,  pageid