Viewing 21-30 of 64 datasets
- 83,978 examples sampled from 10 question answering datasets over text, images and databases.AI2 Israel, Question Understanding • 2020Break is a human annotated dataset of natural language questions and their Question Decomposition Meaning Representations (QDMRs). Break consists of 83,978 examples sampled from 10 question answering datasets over text, images and databases.
- A dataset of 2,985 grade-school level, direct-answer science questions derived from the ARC multiple-choice question set.Aristo • 2020A dataset of 2,985 grade-school level, direct-answer ("open response", "free form") science questions derived from the ARC multiple-choice question set released as part of the AI2 Reasoning Challenge in 2018.
- The largest collection of machine-readable academic papers to date for NLP & text mining.Semantic Scholar • 2019A large corpus of 81.1M English-language academic papers spanning many academic disciplines. Rich metadata, paper abstracts, resolved bibliographic references, as well as structured full text for 8.1M open access papers. Full text annotated with… more
- 24K Question/Answer (QA) pairs over 4.7K paragraphs, split between train (19K QAs), development (2.4K QAs) and a hidden test partition (2.5K QAs).AllenNLP, AI2 Irvine • 2019Quoref is a QA dataset which tests the coreferential reasoning capability of reading comprehension systems. In this span-selection benchmark containing 24K questions over 4.7K paragraphs from Wikipedia, a system must resolve hard coreferences before selecting… more
- 14k QA pairs over 1.7K paragraphs, split between train (10k QAs), development (1.6k QAs) and a hidden test partition (1.7k QAs).AllenNLP, AI2 Irvine • 2019ROPES is a QA dataset which tests a system's ability to apply knowledge from a passage of text to a new situation. A system is presented a background passage containing a causal or qualitative relation(s), a novel situation that uses this background, and… more
- 9,980 8-way multiple-choice questions about grade school scienceAristo • 2019QASC is a question-answering dataset with a focus on sentence composition. It consists of 9,980 8-way multiple-choice questions about grade school science (8,134 train, 926 dev, 920 test), and comes with a corpus of 17M sentences.
- 3864 questions about open domain qualitative relationshipsAristo • 2019QuaRTz is a crowdsourced dataset of 3864 multiple-choice questions about open domain qualitative relationships. Each question is paired with one of 405 different background sentences (sometimes short paragraphs).
- 7,787 multiple choice questions annotated with question classification labelsAristo • 2019A dataset of detailed problem domain classification labels for each of the 7,787 multiple-choice science questions found in the AI2 Reasoning Challenge (ARC) dataset, to enable targeted pairing of questions with problem-specific solvers. Also included is a… more
- Large-scale dataset of 39705 "What if..." questions over procedural textAristo • 2019The WIQA dataset V1 has 39705 questions containing a perturbation and a possible effect in the context of a paragraph. The dataset is split into 29808 train questions, 6894 dev questions and 3003 test questions.
- 12,102 multiple-choice questions with one correct answer and four distractor answersAI2 Israel, Question Understanding • 2019CommonsenseQA is a new multiple-choice question answering dataset that requires different types of commonsense knowledge to predict the correct answers. It contains 12,102 questions with one correct answer and four distractor answers.