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Trivia QA

Paper

Title: TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension Abstract: https://arxiv.org/abs/1705.03551

TriviaQA is a reading comprehension dataset containing over 650K question-answer-evidence triples. TriviaQA includes 95K question-answer pairs authored by trivia enthusiasts and independently gathered evidence documents, six per question on average, that provide high quality distant supervision for answering the questions.

Homepage: https://nlp.cs.washington.edu/triviaqa/

Citation

@InProceedings{JoshiTriviaQA2017,
    author = {Joshi, Mandar and Choi, Eunsol and Weld, Daniel S. and Zettlemoyer, Luke},
    title = {TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension},
    booktitle = {Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics},
    month = {July},
    year = {2017},
    address = {Vancouver, Canada},
    publisher = {Association for Computational Linguistics},
}

Groups and Tasks

Groups

  • Not part of a group yet.

Tasks

  • triviaqa: Generate and answer based on the question.

Checklist

For adding novel benchmarks/datasets to the library:

  • Is the task an existing benchmark in the literature?
    • Have you referenced the original paper that introduced the task?
    • If yes, does the original paper provide a reference implementation? If so, have you checked against the reference implementation and documented how to run such a test?

If other tasks on this dataset are already supported:

  • Is the "Main" variant of this task clearly denoted?
  • Have you provided a short sentence in a README on what each new variant adds / evaluates?
  • Have you noted which, if any, published evaluation setups are matched by this variant?