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
相关论文
共 50 条
  • [41] Recognizing Textual Entailment based on WordNet
    Feng, Jin
    Zhou, Yiming
    Martin, Trevor
    2008 INTERNATIONAL SYMPOSIUM ON INTELLIGENT INFORMATION TECHNOLOGY APPLICATION, VOL II, PROCEEDINGS, 2008, : 27 - +
  • [42] Recognizing Textual Entailment: Models and Applications
    Magnini, Bernardo
    COMPUTATIONAL LINGUISTICS, 2015, 41 (01) : 157 - 160
  • [43] Applying Textual Entailment to the Interpretation of Metaphor
    Mohler, Michael
    Tomlinson, Marc
    Bracewell, David
    2013 IEEE SEVENTH INTERNATIONAL CONFERENCE ON SEMANTIC COMPUTING (ICSC 2013), 2013, : 118 - 125
  • [44] Answer Validation through Textual Entailment
    Pakray, Partha
    NATURAL LANGUAGE PROCESSING AND INFORMATION SYSTEMS, 2011, 6716 : 324 - 329
  • [45] From Alignment to Entailment: A Unified Textual Entailment Framework for Entity Alignment
    Zhao, Yu
    Wu, Yike
    Cai, Xiangrui
    Zhang, Ying
    Zhang, Haiwei
    Yuan, Xiaojie
    FINDINGS OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS (ACL 2023), 2023, : 8795 - 8806
  • [46] Applying COGEX to recognize textual entailment
    Hodges, Daniel
    Clark, Christine
    Fowler, Abraham
    Moldovan, Dan
    MACHINE LEARNING CHALLENGES: EVALUATING PREDICTIVE UNCERTAINTY VISUAL OBJECT CLASSIFICATION AND RECOGNIZING TEXTUAL ENTAILMENT, 2006, 3944 : 427 - 448
  • [47] Paraphrase and Textual Entailment Generation in Czech
    Neveriova, Zuzana
    COMPUTACION Y SISTEMAS, 2014, 18 (03): : 555 - 568
  • [48] Paraphrase substitution for recognizing textual entailment
    Bosma, Wauter
    Callison-Burch, Chris
    EVALUATION OF MULTILINGUAL AND MULTI-MODAL INFORMATION RETRIEVAL, 2007, 4730 : 502 - +
  • [49] Acquiring Data for Textual Entailment Recognition
    Neverilova, Zuzana
    RASLAN 2013: RECENT ADVANCES IN SLAVONIC NATURAL LANGUAGE PROCESSING, 2013, : 29 - 37
  • [50] Annotation Game for Textual Entailment Evaluation
    Neverilova, Zuzana
    COMPUTATIONAL LINGUISTICS AND INTELLIGENT TEXT PROCESSING, CICLING 2014, PT I, 2014, 8403 : 340 - 350
12345