@inproceedings{lai-etal-2017-natural,
    title = "Natural Language Inference from Multiple Premises",
    author = "Lai, Alice  and
      Bisk, Yonatan  and
      Hockenmaier, Julia",
    editor = "Kondrak, Greg  and
      Watanabe, Taro",
    booktitle = "Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 1: Long Papers)",
    month = nov,
    year = "2017",
    address = "Taipei, Taiwan",
    publisher = "Asian Federation of Natural Language Processing",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/I17-1011/",
    pages = "100--109",
    abstract = "We define a novel textual entailment task that requires inference over multiple premise sentences. We present a new dataset for this task that minimizes trivial lexical inferences, emphasizes knowledge of everyday events, and presents a more challenging setting for textual entailment. We evaluate several strong neural baselines and analyze how the multiple premise task differs from standard textual entailment."
}