Building compositional semantics and higher-order inference system for a wide-coverage Japanese CCG parser

Koji Mineshima; Ribeka Tanaka; Pascual Martínez-Gómez; Yusuke Miyao; Daisuke Bekki

doi:10.18653/v1/d16-1242

Building compositional semantics and higher-order inference system for a wide-coverage Japanese CCG parser

Koji Mineshima, Ribeka Tanaka, Pascual Martínez-Gómez, Yusuke Miyao, Daisuke Bekki

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

10 Citations (Scopus)

Abstract

This paper presents a system that compositionally maps outputs of a wide-coverage Japanese CCG parser onto semantic representations and performs automated inference in higher-order logic. The system is evaluated on a textual entailment dataset. It is shown that the system solves inference problems that focus on a variety of complex linguistic phenomena, including those that are difficult to represent in the standard first-order logic.

Original language	English
Title of host publication	EMNLP 2016 - Conference on Empirical Methods in Natural Language Processing, Proceedings
Publisher	Association for Computational Linguistics (ACL)
Pages	2236-2242
Number of pages	7
ISBN (Electronic)	9781945626258
DOIs	https://doi.org/10.18653/v1/d16-1242
Publication status	Published - 2016
Externally published	Yes
Event	2016 Conference on Empirical Methods in Natural Language Processing, EMNLP 2016 - Austin, United States Duration: 2016 Nov 1 → 2016 Nov 5

Publication series

Name	EMNLP 2016 - Conference on Empirical Methods in Natural Language Processing, Proceedings

Conference

Conference	2016 Conference on Empirical Methods in Natural Language Processing, EMNLP 2016
Country/Territory	United States
City	Austin
Period	16/11/1 → 16/11/5

ASJC Scopus subject areas

Computer Science Applications
Information Systems
Computational Theory and Mathematics

Access to Document

10.18653/v1/d16-1242

Cite this

Mineshima, K., Tanaka, R., Martínez-Gómez, P., Miyao, Y., & Bekki, D. (2016). Building compositional semantics and higher-order inference system for a wide-coverage Japanese CCG parser. In EMNLP 2016 - Conference on Empirical Methods in Natural Language Processing, Proceedings (pp. 2236-2242). (EMNLP 2016 - Conference on Empirical Methods in Natural Language Processing, Proceedings). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/d16-1242

Building compositional semantics and higher-order inference system for a wide-coverage Japanese CCG parser. / Mineshima, Koji; Tanaka, Ribeka; Martínez-Gómez, Pascual et al.
EMNLP 2016 - Conference on Empirical Methods in Natural Language Processing, Proceedings. Association for Computational Linguistics (ACL), 2016. p. 2236-2242 (EMNLP 2016 - Conference on Empirical Methods in Natural Language Processing, Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Mineshima, K, Tanaka, R, Martínez-Gómez, P, Miyao, Y & Bekki, D 2016, Building compositional semantics and higher-order inference system for a wide-coverage Japanese CCG parser. in EMNLP 2016 - Conference on Empirical Methods in Natural Language Processing, Proceedings. EMNLP 2016 - Conference on Empirical Methods in Natural Language Processing, Proceedings, Association for Computational Linguistics (ACL), pp. 2236-2242, 2016 Conference on Empirical Methods in Natural Language Processing, EMNLP 2016, Austin, United States, 16/11/1. https://doi.org/10.18653/v1/d16-1242

Mineshima K, Tanaka R, Martínez-Gómez P, Miyao Y, Bekki D. Building compositional semantics and higher-order inference system for a wide-coverage Japanese CCG parser. In EMNLP 2016 - Conference on Empirical Methods in Natural Language Processing, Proceedings. Association for Computational Linguistics (ACL). 2016. p. 2236-2242. (EMNLP 2016 - Conference on Empirical Methods in Natural Language Processing, Proceedings). doi: 10.18653/v1/d16-1242

Mineshima, Koji ; Tanaka, Ribeka ; Martínez-Gómez, Pascual et al. / Building compositional semantics and higher-order inference system for a wide-coverage Japanese CCG parser. EMNLP 2016 - Conference on Empirical Methods in Natural Language Processing, Proceedings. Association for Computational Linguistics (ACL), 2016. pp. 2236-2242 (EMNLP 2016 - Conference on Empirical Methods in Natural Language Processing, Proceedings).

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abstract = "This paper presents a system that compositionally maps outputs of a wide-coverage Japanese CCG parser onto semantic representations and performs automated inference in higher-order logic. The system is evaluated on a textual entailment dataset. It is shown that the system solves inference problems that focus on a variety of complex linguistic phenomena, including those that are difficult to represent in the standard first-order logic.",

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Building compositional semantics and higher-order inference system for a wide-coverage Japanese CCG parser

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