code: def preprocess_boolq(examples: Dataset) -> Dict[str, List[str]]:
      """BoolQ preprocessing to be applied by the map function. The preprocessing boils down
      to removing redundant titles from the passages.
      Args:
          examples: an instance of Dataset class
      Returns:
          Dict[str, List[str]]: processed features (just the passage in this case)
      """
  
      def remove_passage_title(passage: str) -> str:
          """Removes the title of a given passage. The motivation is that the title duplicates
          the beginning of the text body, which means that it's redundant. We remove to save space.
          Args:
              passage: a single `passage` string
          Returns:
              str: the same `passage` string with the title removed
          """
          return re.sub(r"^.+-- ", "", passage)
  
      passages = [
          remove_passage_title(passage)
          for passage in examples["passage"]
      ]
  
      return {"passage": passages}
  
file_path: DeepPavlov/deeppavlov/dataset_readers/huggingface_dataset_reader.py
imports: import re
  from collections import Counter
  from math import floor
  from typing import Dict, Optional, List, Union
  from datasets import load_dataset, Dataset, Features, ClassLabel, concatenate_datasets
  from deeppavlov.core.common.registry import register
  from deeppavlov.core.data.dataset_reader import DatasetReader
label_desc: Use image node_id 3 for calling a global function with example usage: preprocess_boolq(examples) and returns: dict, re