• DOI:10.18653/v1/P19-1484
Corpus ID: 186206974

Unsupervised Question Answering by Cloze Translation

@article{Lewis2019UnsupervisedQA,
  title={Unsupervised Question Answering by Cloze Translation},
  author={Patrick Lewis and Ludovic Denoyer and S. Riedel},
  journal={ArXiv},
  year={2019},
  volume={abs/1906.04980}
}

Patrick Lewis, Ludovic Denoyer, S. Riedel

Published 2019

Computer Science

ArXiv

Obtaining training data for Question Answering (QA) is time-consuming and resource-intensive, and existing QA datasets are only available for limited domains and languages. [...] Key Method To generate such triples, we first sample random context paragraphs from a large corpus of documents and then random noun phrases or named entity mentions from these paragraphs as answers. Next we convert answers in context to "fill-in-the-blank" cloze questions and finally translate them into natural questions.Expand Abstract

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