QNP Textual Entailment with Polynomial Event Semantics

被引：2
|
作者：
Kiselyov, Oleg [1 ]
Watanabe, Haruki [1 ]
机构：
[1] Tohoku Univ, Sendai, Miyagi, Japan
来源：
NEW FRONTIERS IN ARTIFICIAL INTELLIGENCE, JSAI-ISAI 2021 WORKSHOPS, JURISIN 2021, LENLS18, SCIDOCA 2021, KANSEI-AI 2021, AND AI-BIZ 2021 | 2023年 / 13856卷
关键词：
D O I：
10.1007/978-3-031-36190-6_14
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
FraCaS textual entailment corpus has become the standard benchmark for semantics theories, in particular, theories of quantification (Sect. 1 of FraCaS). Here we apply it to polynomial event semantics: the latest approach to combining quantification and Neo-Davidsonian event semantics, maintaining compositionality and the in situ analysis of quantifiers. Although several FraCaS problems look custom-made for the polynomial events semantics, there are challenges: the variety of generalized quantifiers (including 'many', 'most' and 'few'); copula, existence, and relative clauses. We address them in this paper.
引用
收藏
页码：198 / 211
页数：14
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