Exploiting Open IE for Deriving Multiple Premises Entailment Corpus

Martin Vita, Jakub Klímek
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引用次数: 1

Abstract

Natural language inference (NLI) is a key part of natural language understanding. The NLI task is defined as a decision problem whether a given sentence – hypothesis – can be inferred from a given text. Typically, we deal with a text consisting of just a single premise/single sentence, which is called a single premise entailment (SPE) task. Recently, a derived task of NLI from multiple premises (MPE) was introduced together with the first annotated corpus and corresponding several strong baselines. Nevertheless, the further development in MPE field requires accessibility of huge amounts of annotated data. In this paper we introduce a novel method for rapid deriving of MPE corpora from an existing NLI (SPE) annotated data that does not require any additional annotation work. This proposed approach is based on using an open information extraction system. We demonstrate the application of the method on a well known SNLI corpus. Over the obtained corpus, we provide the first evaluations as well as we state a strong baseline.
利用开放IE获取多前提蕴涵语料库
自然语言推理是自然语言理解的重要组成部分。NLI任务被定义为一个判断问题,即是否可以从给定的文本中推断出给定的句子或假设。通常,我们处理仅由单个前提/单个句子组成的文本,这称为单个前提蕴涵(SPE)任务。最近,引入了一个衍生的多前提NLI任务(MPE),以及第一个标注语料库和相应的几个强基线。然而,MPE领域的进一步发展需要大量注释数据的可访问性。本文介绍了一种从已有的NLI (SPE)注释数据中快速提取MPE语料库的新方法,该方法不需要任何额外的注释工作。该方法基于使用一个开放的信息提取系统。我们演示了该方法在一个著名的SNLI语料库上的应用。在获得的语料库上,我们提供了第一次评估,并声明了一个强大的基线。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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