code: def _get_question(
      topic_id, topic_name, test_id, document_id, document_str, question
  ):
      """Gets instance ID and features for every question.
  
      Args:
        topic_id: string
        topic_name: string
        test_id: string
        document_id: string
        document_str: string
        question: XML element for question
  
      Returns:
        id_: string. Unique ID for instance.
        feats: dict of instance features
      """
  
      question_id = question.attrib["q_id"]
      for q_text in question.iter("q_str"):
          question_str = q_text.text
      possible_answers = list()
      for answer in question.iter("answer"):
          answer_id = answer.attrib["a_id"]
          answer_str = answer.text
          possible_answers.append(
              {"answer_id": answer_id, "answer_str": answer_str}
          )
          if "correct" in answer.attrib:
              correct_answer_id = answer_id
              correct_answer_str = answer_str
  
      id_ = "_".join([topic_id, topic_name, test_id, question_id])
      logging.info("ID: %s", id_)
  
      feats = {
          "topic_id": topic_id,
          "topic_name": topic_name,
          "test_id": test_id,
          "document_id": document_id,
          "document_str": document_str,
          "question_id": question_id,
          "question_str": question_str,
          "answer_options": possible_answers,
          "correct_answer_id": correct_answer_id,
          "correct_answer_str": correct_answer_str,
      }
  
      return id_, feats
  
file_path: datasets/tensorflow_datasets/datasets/qa4mre/qa4mre_dataset_builder.py
imports: import os
  import xml.etree.ElementTree
  from absl import logging
  from tensorflow_datasets.core.utils.lazy_imports_utils import tensorflow
  import tensorflow_datasets.public_api
label_desc: Use image node_id 1 for calling a global function with example usage: _get_question(topic_id, topic_name, test_id, document_id, document_str, question) and returns: id_,  feats