code: def normalize_answer(s, lang):
      """Lower text and remove punctuation, articles and extra whitespace."""
  
      def remove_articles(text, inner_lang):
          if inner_lang == "en":
              return re.sub(r"\b(a|an|the)\b", " ", text)
          elif inner_lang == "es":
              return re.sub(
                  r"\b(un|una|unos|unas|el|la|los|las)\b", " ", text
              )
          elif inner_lang == "hi":
              return text  # Hindi does not have formal articles
          elif inner_lang == "vi":
              return re.sub(r"\b(của|là|cái|chiếc|những)\b", " ", text)
          elif inner_lang == "de":
              return re.sub(
                  r"\b(ein|eine|einen|einem|eines|einer|der|die|das|den|dem|des)\b",
                  " ",
                  text,
              )
          elif inner_lang == "ar":
              return re.sub("\sال^|ال", " ", text)  # noqa: W605
          elif inner_lang == "zh":
              return text  # Chinese does not have formal articles
          else:
              raise Exception("Unknown Language {}".format(inner_lang))
  
      def white_space_fix(text, inner_lang):
          if inner_lang in WHITESPACE_LANGS:
              tokens = whitespace_tokenize(text)
          elif inner_lang in MIXED_SEGMENTATION_LANGS:
              tokens = mixed_segmentation(text)
          else:
              raise Exception("Unknown Language {}".format(inner_lang))
          return " ".join([t for t in tokens if t.strip() != ""])
  
      def remove_punc(text):
          return "".join(ch for ch in text if ch not in PUNCT)
  
      def lower(text):
          return text.lower()
  
      return white_space_fix(
          remove_articles(remove_punc(lower(s)), lang), lang
      )
  
imports: import string
  import re
  import sys
  import unicodedata
  from collections import Counter
  from dataclasses import dataclass
  from jiant.tasks.lib.templates.squad_style import core
label_desc: Use image node_id 3 for calling a global function with example usage: normalize_answer(s, lang) and returns: white_space_fix, str, str, text, re, re, text, re, re, re, text