code: def _prepare_examples(texts_file_path, annot_file_path, day_str):
      """Prepares examples for 1 day."""
      # Read raw data
      raw_texts = _read_texts_file(texts_file_path)
      annotations = _read_annot_file(annot_file_path)
  
      # Construct replies graph
      idx_to_parents = {idx: [] for idx in range(len(raw_texts))}
      for parent_msg_idx, msg_idx in annotations:
          idx_to_parents[msg_idx].append(parent_msg_idx)
  
      texts, timestamps = _parse_out_timestamps(raw_texts, day_str)
  
      for line_idx, parents in idx_to_parents.items():
          parents_ids = [
              _get_msg_id(day_str, parent) for parent in parents
          ]
          yield {
              _MESSAGE_ID: _get_msg_id(day_str, line_idx),
              _MESSAGE_TEXT: texts[line_idx],
              _MESSAGE_TIMESTAMP: timestamps[line_idx],
              _MESSAGE_PARENTS_IDS: parents_ids,
          }
  
file_path: datasets/tensorflow_datasets/datasets/irc_disentanglement/irc_disentanglement_dataset_builder.py
imports: import collections
  import os
  from typing import List
  from tensorflow_datasets.core.utils.lazy_imports_utils import tensorflow
  import tensorflow_datasets.public_api
label_desc: Use image node_id 6 for calling a global function with example usage: _prepare_examples(texts_file_path, annot_file_path, day_str) without return types