code: def normalize_cap(option, pron):
      """Normalize the capitalization of the option according to the pronoun."""
      cap_tuples = [
          ("The", "the"),
          ("His", "his"),
          ("My", "my"),
          ("Her", "her"),
          ("Their", "their"),
          ("An", "an"),
          ("A", "a"),
      ]
      uncap_dict = dict(cap_tuples)
      cap_dict = dict([(t[1], t[0]) for t in cap_tuples])
      words = option.split(" ")
      first_word = words[0]
      if pron[0].islower():
          first_word = uncap_dict.get(first_word, first_word)
      else:
          first_word = cap_dict.get(first_word, first_word)
      words[0] = first_word
      option = " ".join(words)
      return option
  
file_path: datasets/tensorflow_datasets/text/wsc273/wsc273.py
imports: from __future__ import annotations
  import numpy
  import tensorflow_datasets.public_api
label_desc: Use image node_id 2 for calling a global function with example usage: normalize_cap(option, pron) and returns: option