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.
@article{arxiv.1710.02925,
title = {Natural Language Inference from Multiple Premises},
author = {Alice Lai and Yonatan Bisk and Julia Hockenmaier},
journal= {arXiv preprint arXiv:1710.02925},
year = {2017}
}