Viewing 21-30 of 34 datasets
- 1,197,377 science-relevant sentencesAristo • 2016The Aristo Mini corpus contains 1,197,377 (very loosely) science-relevant sentences drawn from public data. It provides simple science-relevant text that may be useful to help answer elementary science questions.
- 1,363 gold explanation sentencesAristo • 2016This dataset contains gold explanation sentences supporting 363 science questions, relation annotation for a subset of those explanations, and a graphical annotation tool with annotation guidelines.
- 4,817 imagesPRIOR • 2016AI2D is a dataset of illustrative diagrams for research on diagram understanding and associated question answering.
- 1,080 questionsAristo • 2016These questions were created using the "AI2 Elementary School Science Questions (No Diagrams)" data set by changing all of the incorrect answer options of each question with some other related word. This dataset can be a good measure of robustness for QA systems when being testing on modified questions.
- 9,850 videosPRIOR • 2016This dataset guides our research into unstructured video activity recognition and commonsense reasoning for daily human activities. These videos of daily indoors activities were collected through Amazon Mechanical Turk.
- 9092 crowd-sourced science questions and 68 tables of curated factsAristo • 2016This dataset contains a copy of the Aristo Tablestore (Nov. 2015 Snapshot), plus a large set of crowd-sourced multiple-choice questions covering the facts in the tables. Through the setup of the crowd-sourced annotation task, the package also contains implicit alignment information between questions and tables.
- 68 tables of curated factsAristo • 2015This dataset contains a collection of curated facts in the form of tables used by the Aristo Question-Answering System, collected using a mixture of manual and semi-automated techniques.
- 81 dialog traces and extractionsAristo • 2015This dataset contains files for the paper "Learning knowledge graphs for question answering through conversational dialog", presented at the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL 2015), Denver, Colorado. May 31 - June 5, 2015.
- Evaluations for 108 real science exam questionsAristo • 2015This work explores the use of Markov Logic Networks (MLNs) for answering elementary-level natural language science questions. The dataset contains the MLNs generated from three different formulations along with a README describing the format.
- 391 arithmetic questions2014These questions guide our research into Question Answering for arithmetic exams. Focus is on high school level questions.