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dc.contributor.authorBowman, Samuel R.-
dc.contributor.authorAngeli, Gabor-
dc.contributor.authorPotts, Christopher-
dc.contributor.authorManning, Christopher D.-
dc.date.accessioned2018-03-28T16:30:15Z-
dc.date.available2018-03-28T16:30:15Z-
dc.date.issued2015-06-
dc.identifier.citationSamuel R. Bowman, Gabor Angeli, Christopher Potts, and Christopher D. Manning. 2015. A large annotated corpus for learning natural language inference. In Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing (EMNLP).en
dc.identifier.urihttp://hdl.handle.net/2451/41728-
dc.description.abstractThe SNLI corpus (version 1.0) is a collection of 570k human-written English sentence pairs manually labeled for balanced classification with the labels entailment, contradiction, and neutral, supporting the task of natural language inference (NLI), also known as recognizing textual entailment (RTE). We aim for it to serve both as a benchmark for evaluating representational systems for text, especially including those induced by representation learning methods, as well as a resource for developing NLP models of any kind.en
dc.description.sponsorshipWe gratefully acknowledge support from a Google Faculty Research Award, a gift from Bloomberg L.P., the Defense Advanced Research Projects Agency (DARPA) Deep Exploration and Filtering of Text (DEFT) Program under Air Force Research Laboratory (AFRL) contract no. FA8750-13-2-0040, the National Science Foundation under grant no. IIS 1159679, and the Department of the Navy, Office of Naval Research, under grant no. N00014-10-1-0109. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of Google, Bloomberg L.P., DARPA, AFRL NSF, ONR, or the US government. We also thank our many excellent Mechanical Turk contributors.en
dc.language.isoenen
dc.rightsDataset licensed as CC-BY-SA 4.0. Paper licensed as CC-BY-NC-SA 3.0en
dc.titleThe SNLI Corpusen
dc.typeDataseten
dc.typePreprinten
Appears in Collections:Machine Learning for Language Lab

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snli_1.0.zipSNLI 1.0 (data, zip)92.33 MBUnknownView/Open
snli_paper.pdfSNLI description paper (PDF)248.05 kBAdobe PDFView/Open
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