@inproceedings{vashishtha-etal-2020-temporal,
    title = "Temporal Reasoning in Natural Language Inference",
    author = "Vashishtha, Siddharth  and
      Poliak, Adam  and
      Lal, Yash Kumar  and
      Van Durme, Benjamin  and
      White, Aaron Steven",
    booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2020",
    month = nov,
    year = "2020",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/2020.findings-emnlp.363",
    doi = "10.18653/v1/2020.findings-emnlp.363",
    pages = "4070--4078",
    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.",
}