{"url":"/dataset/conditionalqa","name":"ConditionalQA","full_name":null,"description_markdown":"ConditionalQA is a Question Answering (QA) dataset that contains complex questions with conditional answers, i.e. the answers are only applicable when certain conditions apply.","description_withheld":null,"homepage":"https://haitian-sun.github.io/conditionalqa/","introduced_date":"2021-10-13","introduced_date_note":null,"introduced_by":{"paper":"/paper/conditionalqa-a-complex-reading-comprehension","title":"ConditionalQA: A Complex Reading Comprehension Dataset with Conditional Answers","first_author":"Haitian Sun","url":null},"license":{"name":"CC BY-SA 4.0","url":"https://creativecommons.org/licenses/by-sa/4.0/"},"modalities":[{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[{"name":"Question Answering","url":"/task/question-answering","datasets_with_task":"/datasets/task/question-answering"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["ConditionalQA"],"data_loaders":[{"repo":"https://github.com/haitian-sun/conditionalqa","url":"https://github.com/haitian-sun/conditionalqa","frameworks":[]}],"num_papers_in_archive":12,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/question-answering-on-conditionalqa","task":"Question Answering","dataset_variant":"ConditionalQA","rows":3,"metrics":["Conditional (answers)","Conditional (w/ conditions)","Overall (answers)","Overall (w/ conditions)"],"first_row_in_archive_order":{"model":"FiD","paper":"/paper/leveraging-passage-retrieval-with-generative","metrics":{"Conditional (answers)":"45.2 / 49.7","Conditional (w/ conditions)":"4.7 / 5.8","Overall (answers)":"44.4 / 50.8","Overall (w/ conditions)":"35.0 / 40.6"},"code_links":[{"title":"jhyuklee/DensePhrases","url":"https://github.com/jhyuklee/DensePhrases"},{"title":"princeton-nlp/DensePhrases","url":"https://github.com/princeton-nlp/DensePhrases"},{"title":"facebookresearch/FiD","url":"https://github.com/facebookresearch/FiD"},{"title":"amzn/refuel-open-domain-qa","url":"https://github.com/amzn/refuel-open-domain-qa"},{"title":"uclnlp/APE","url":"https://github.com/uclnlp/APE"},{"title":"xfactlab/emnlp2023-damaging-retrieval","url":"https://github.com/xfactlab/emnlp2023-damaging-retrieval"},{"title":"ZIZUN/MAFiD","url":"https://github.com/ZIZUN/MAFiD"},{"title":"FenQQQ/Fusion-in-decoder","url":"https://github.com/FenQQQ/Fusion-in-decoder"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/end-to-end-multihop-retrieval-for","title":"Iterative Hierarchical Attention for Answering Complex Questions over Long Documents","date":"2021-06-01","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/leveraging-passage-retrieval-with-generative","title":"Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering","date":"2020-07-02","rows_on_this_dataset":1,"code_links":8,"syntology":null},{"paper":"/paper/etc-encoding-long-and-structured-data-in","title":"ETC: Encoding Long and Structured Inputs in Transformers","date":"2020-04-17","rows_on_this_dataset":1,"code_links":2,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":1,"samples_ran":1,"samples_unverified":0,"pointer_only_for_licence":1,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":1,"samples_harvested":1,"samples_ran":1,"samples_unverified":0,"pointer_only_for_licence":1,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}