基于图式的文本蕴涵识别初探

A Tentative Study on Schemata Based Textual Entailment Recognition

文本蕴涵识别是大部分自然语言信息处理应用的核心。该文尝试探讨文本蕴涵识别中涉及的(意象)图式理据。通过对选自语料例子的分析,显示各类图式是如何成为文本蕴涵识别的理据的。图式包括物性结构、理想认知模型、框架、脚本等。这些图式都是表示语义信息的结构。从广义上讲它们都可以纳入语义特征的范畴,都可能成为蕴涵关系成立的理据。基于图式的文本蕴涵识别研究结合有关图式库的构建,有望为突破文本蕴涵识别瓶颈作出重要贡献。

Recognition of Textual Entailment （RTE） is of substantial significance to most natural language process- ing. This paper explores the schematic explanations to TE, revealing how （image） schemata can justify the TE re- sults by case studies. Schemata include qualia structure, idealized cognitive model, and frame, script, etc. , all of which are structures that can be used for representing word meaning. In a broad sense, all these kinds of schemata belong to the category of semantic feature and thus have the potential to become evidences for TE. Exploration into RTE based on schemata and the construction of corresponding corpora of schemata may contribute to solving the bottleneck issues in RTE.