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Temporal Reasoning in Natural Language Inference

2020-11-01Findings of the Association for Computational LinguisticsCode Available0· sign in to hype

Siddharth Vashishtha, Adam Poliak, Yash Kumar Lal, Benjamin Van Durme, Aaron Steven White

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Abstract

We introduce five new natural language inference (NLI) datasets focused on temporal reasoning. We recast four existing datasets annotated for event duration---how long an event lasts---and event ordering---how events are temporally arranged---into more than one million NLI examples. We use these datasets to investigate how well neural models trained on a popular NLI corpus capture these forms of temporal reasoning.

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