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Are Natural Language Inference Models IMPPRESsive? Learning IMPlicature and PRESupposition
2020
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
unpublished
Natural language inference (NLI) is an increasingly important task for natural language understanding, which requires one to infer whether a sentence entails another. However, the ability of NLI models to make pragmatic inferences remains understudied. We create an IMPlicature and PRESupposition diagnostic dataset (IMPPRES), consisting of >25k semiautomatically generated sentence pairs illustrating well-studied pragmatic inference types. We use IMPPRES to evaluate whether BERT, InferSent, and
doi:10.18653/v1/2020.acl-main.768
fatcat:ytu7vlgsn5cjtndgrw7kpqet54