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Datasets/Natural Questions

Natural Questions

TextsCC BY-SA 3.0Introduced 2019-01-01

The Natural Questions corpus is a question answering dataset containing 307,373 training examples, 7,830 development examples, and 7,842 test examples. Each example is comprised of a google.com query and a corresponding Wikipedia page. Each Wikipedia page has a passage (or long answer) annotated on the page that answers the question and one or more short spans from the annotated passage containing the actual answer. The long and the short answer annotations can however be empty. If they are both empty, then there is no answer on the page at all. If the long answer annotation is non-empty, but the short answer annotation is empty, then the annotated passage answers the question but no explicit short answer could be found. Finally 1% of the documents have a passage annotated with a short answer that is “yes” or “no”, instead of a list of short spans.

Source: A BERT Baseline for the Natural Questions Image Source: https://paperswithcode.com/paper/natural-questions-a-benchmark-for-question/

Benchmarks

Information Retrieval/Precision@100Information Retrieval/Precision@20Open-Domain Question Answering/Exact MatchQuestion Answering/EMQuestion Answering/Exact MatchQuestion Generation/QAEQuestion Generation/R-QAERetrieval/Queries per secondRetrieval/NDCG@10

Related Benchmarks

Natural Questions (long)/Question Answering/EMNatural Questions (long)/Question Answering/F1Natural Questions (short)/Open-Domain Question Answering/Exact MatchNatural Questions (short)/Question Answering/Exact Match

Statistics

Papers
1,404
Benchmarks
9

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Tasks

Information RetrievalOpen-Domain Question AnsweringPassage RetrievalQuestion AnsweringQuestion GenerationRetrievalText RetrievalZero-shot Text Search