2019 NaturalQuestionsABenchmarkforQu

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Subject Headings: Natural Questions Dataset; Question-Answering Dataset; GPT-2 Benchmark Task.

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Abstract

We present the Natural Questions corpus, a question answering dataset. Questions consist of real anonymized, aggregated queries issued to the Google search engine. An annotator is presented with a question along with a Wikipedia page from the top 5 search results, and annotates a long answer (typically a paragraph) and a short answer (one or more entities) if present on the page, or marks null if no long/short answer is present. The public release consists of 307,373 training examples with single annotations; 7,830 examples with 5-way annotations for development data; and a further 7,842 examples 5-way annotated sequestered as test data. We present experiments validating quality of the data. We also describe analysis of 25-way annotations on 302 examples, giving insights into human variability on the annotation task. We introduce robust metrics for the purposes of evaluating question answering systems; demonstrate high human upper bounds on these metrics; and establish baseline results using competitive methods drawn from related literature.

References

BibTeX

@article{2019_NaturalQuestionsABenchmarkforQu,
  author    = {Tom Kwiatkowski and
               Jennimaria Palomaki and
               Olivia Redfield and
               Michael Collins and
               Ankur P. Parikh and
               Chris Alberti and
               Danielle Epstein and
               Illia Polosukhin and
               Jacob Devlin and
               Kenton Lee and
               Kristina Toutanova and
               Llion Jones and
               Matthew Kelcey and
               Ming-Wei Chang and
               Andrew M. Dai and
               Jakob Uszkoreit and
               Quoc Le and
               Slav Petrov},
  title     = {Natural Questions: a Benchmark for Question Answering Research},
  journal   = {Transactions of the Association for Computational Linguistics},
  volume    = {7},
  pages     = {452--466},
  year      = {2019},
  url       = {https://transacl.org/ojs/index.php/tacl/article/view/1455},
}


 AuthorvolumeDate ValuetitletypejournaltitleUrldoinoteyear
2019 NaturalQuestionsABenchmarkforQuMichael Collins
Ming-Wei Chang
Slav Petrov
Chris Alberti
Kristina Toutanova
Andrew M. Dai
Jakob Uszkoreit
Llion Jones
Illia Polosukhin
Ankur P. Parikh
Jacob Devlin
Kenton Lee
Quoc Le
Tom Kwiatkowski
Jennimaria Palomaki
Olivia Redfield
Danielle Epstein
Matthew Kelcey
Natural Questions: A Benchmark for Question Answering Research2019