{"url":"/dataset/subjqa","name":"SubjQA","full_name":null,"description_markdown":"**SubjQA** is a question answering dataset that focuses on subjective (as opposed to factual) questions and answers. The dataset consists of roughly 10,000 questions over reviews from 6 different domains: books, movies, grocery, electronics, TripAdvisor (i.e. hotels), and restaurants. Each question is paired with a review and a span is highlighted as the answer to the question (with some questions having no answer). Moreover, both questions and answer spans are assigned a subjectivity label by annotators. Questions such as \"How much does this product weigh?\" is a factual question (i.e., low subjectivity), while \"Is this easy to use?\" is a subjective question (i.e., high subjectivity).\n\nSource: [https://github.com/megagonlabs/SubjQA](https://github.com/megagonlabs/SubjQA)","description_withheld":null,"homepage":"https://github.com/megagonlabs/SubjQA","introduced_date":null,"introduced_date_note":null,"introduced_by":{"paper":"/paper/subjqa-a-dataset-for-subjectivity-and-review","title":"SubjQA: A Dataset for Subjectivity and Review Comprehension","first_author":"Johannes Bjerva","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":"Sentiment Analysis","url":"/task/sentiment-analysis","datasets_with_task":"/datasets/task/sentiment-analysis"},{"name":"Word Sense Disambiguation","url":"/task/word-sense-disambiguation","datasets_with_task":"/datasets/task/word-sense-disambiguation"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["SubjQA"],"data_loaders":[{"repo":"https://github.com/huggingface/datasets","url":"https://huggingface.co/datasets/megagonlabs/subjqa","frameworks":["tf","pytorch","jax"]},{"repo":"https://github.com/huggingface/datasets","url":"https://huggingface.co/datasets/subjqa","frameworks":["tf","pytorch","jax"]},{"repo":"https://github.com/megagonlabs/SubjQA","url":"https://github.com/megagonlabs/SubjQA","frameworks":[]}],"num_papers_in_archive":8,"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."}