{"url":"/dataset/protoqa","name":"ProtoQA","full_name":null,"description_markdown":"**ProtoQA** is a question answering dataset for training and evaluating common sense reasoning capabilities of artificial intelligence systems in such prototypical situations. The training set is gathered from an existing set of questions played in a long-running international game show FAMILY- FEUD. The hidden evaluation set is created by gathering answers for each question from 100 crowd-workers.\n\nSource: [https://github.com/iesl/protoqa-data](https://github.com/iesl/protoqa-data)","description_withheld":null,"homepage":"https://github.com/iesl/protoqa-data","introduced_date":null,"introduced_date_note":null,"introduced_by":{"paper":"/paper/protoqa-a-question-answering-dataset-for","title":"ProtoQA: A Question Answering Dataset for Prototypical Common-Sense Reasoning","first_author":"Michael Boratko","url":null},"license":null,"modalities":[{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[{"name":"Question Answering","url":"/task/question-answering","datasets_with_task":"/datasets/task/question-answering"},{"name":"Common Sense Reasoning","url":"/task/common-sense-reasoning","datasets_with_task":"/datasets/task/common-sense-reasoning"}],"languages":[],"variants":["ProtoQA"],"data_loaders":[{"repo":"https://github.com/huggingface/datasets","url":"https://huggingface.co/datasets/community-datasets/proto_qa","frameworks":["tf","pytorch","jax"]},{"repo":"https://github.com/huggingface/datasets","url":"https://huggingface.co/datasets/proto_qa","frameworks":["tf","pytorch","jax"]},{"repo":"https://github.com/iesl/protoqa-data","url":"https://github.com/iesl/protoqa-data","frameworks":[]}],"num_papers_in_archive":11,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"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."}