code: def load_wikiqa():
        # noqa
  
      dataset_path = _load('wikiqa')
  
      data = _load_csv(dataset_path, 'data', set_index=True)
      questions = _load_csv(dataset_path, 'questions', set_index=True)
      sentences = _load_csv(dataset_path, 'sentences', set_index=True)
      vocabulary = _load_csv(dataset_path, 'vocabulary', set_index=True)
  
      entities = {
          'data': (data, 'd3mIndex', None),
          'questions': (questions, 'qIndex', None),
          'sentences': (sentences, 'sIndex', None),
          'vocabulary': (vocabulary, 'index', None)
      }
      relationships = [
          ('questions', 'qIndex', 'data', 'qIndex'),
          ('sentences', 'sIndex', 'data', 'sIndex')
      ]
  
      target = data.pop('isAnswer').values
  
      return Dataset(load_wikiqa.__doc__, data, target, accuracy_score, startify=True,
                     entities=entities, relationships=relationships)
docs: A Challenge Dataset for Open-Domain Question Answering.
  
      WikiQA dataset is a publicly available set of question and sentence (QS) pairs,
      collected and annotated for research on open-domain question answering.
  
      source: "Microsoft"
      sourceURI: "https://www.microsoft.com/en-us/research/publication/wikiqa-a-challenge-dataset-for-open-domain-question-answering/#"