Corpus ID: 11606382

SearchQA: A New Q&A Dataset Augmented with Context from a Search Engine

@article{Dunn2017SearchQAAN,
  title={SearchQA: A New Q&A Dataset Augmented with Context from a Search Engine},
  author={M. Dunn and Levent Sagun and M. Higgins and V. U. G{\"u}ney and Volkan Cirik and Kyunghyun Cho},
  journal={ArXiv},
  year={2017},
  volume={abs/1704.05179}
}
  • M. Dunn, Levent Sagun, +3 authors Kyunghyun Cho
  • Published 2017
  • Computer Science
  • ArXiv
  • We publicly release a new large-scale dataset, called SearchQA, for machine comprehension, or question-answering. [...] Key Method Following this approach, we built SearchQA, which consists of more than 140k question-answer pairs with each pair having 49.6 snippets on average. Each question-answer-context tuple of the SearchQA comes with additional meta-data such as the snippet's URL, which we believe will be valuable resources for future research. We conduct human evaluation as well as test two baseline…Expand Abstract

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