Chinese semantic role labeling using high-quality syntactic knowledge

Gongye Jin; Daisuke Kawahara; Sadao Kurohashi

Chinese semantic role labeling using high-quality syntactic knowledge

Gongye Jin, Daisuke Kawahara, Sadao Kurohashi

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

Abstract

This paper presents an application of Chinese syntactic knowledge for semantic role labeling (SRL). Besides basic morphological information, syntactic structures are crucial in SRL. However, it is difficult to learn such information from limited, small-scale, manually annotated training data. Instead of manually increasing the size of annotated data, we use a large amount of automatically extracted syntactic knowledge to improve the performance of SRL.

Original language	English
Title of host publication	Proceedings of the 8th SIGHAN Workshop on Chinese Language Processing, SIGHAN 2015 - co-located with 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing, ACL IJCNLP 2015
Editors	Liang-Chih Yu, Zhifang Sui, Yue Zhang, Vincent Ng
Publisher	Association for Computational Linguistics (ACL)
Pages	120-127
Number of pages	8
ISBN (Electronic)	9781941643570
Publication status	Published - 2015
Externally published	Yes
Event	8th SIGHAN Workshop on Chinese Language Processing, SIGHAN 2015 - Beijing, China Duration: 2015 Jul 30 → 2015 Jul 31

Publication series

Name	Proceedings of the 8th SIGHAN Workshop on Chinese Language Processing, SIGHAN 2015 - co-located with 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing, ACL IJCNLP 2015

Conference

Conference	8th SIGHAN Workshop on Chinese Language Processing, SIGHAN 2015
Country/Territory	China
City	Beijing
Period	15/7/30 → 15/7/31

ASJC Scopus subject areas

Language and Linguistics
Computer Science Applications
Education
Linguistics and Language

Cite this

Jin, G., Kawahara, D., & Kurohashi, S. (2015). Chinese semantic role labeling using high-quality syntactic knowledge. In L-C. Yu, Z. Sui, Y. Zhang, & V. Ng (Eds.), Proceedings of the 8th SIGHAN Workshop on Chinese Language Processing, SIGHAN 2015 - co-located with 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing, ACL IJCNLP 2015 (pp. 120-127). (Proceedings of the 8th SIGHAN Workshop on Chinese Language Processing, SIGHAN 2015 - co-located with 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing, ACL IJCNLP 2015). Association for Computational Linguistics (ACL).

Chinese semantic role labeling using high-quality syntactic knowledge. / Jin, Gongye; Kawahara, Daisuke; Kurohashi, Sadao.
Proceedings of the 8th SIGHAN Workshop on Chinese Language Processing, SIGHAN 2015 - co-located with 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing, ACL IJCNLP 2015. ed. / Liang-Chih Yu; Zhifang Sui; Yue Zhang; Vincent Ng. Association for Computational Linguistics (ACL), 2015. p. 120-127 (Proceedings of the 8th SIGHAN Workshop on Chinese Language Processing, SIGHAN 2015 - co-located with 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing, ACL IJCNLP 2015).

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

Jin, G, Kawahara, D & Kurohashi, S 2015, Chinese semantic role labeling using high-quality syntactic knowledge. in L-C Yu, Z Sui, Y Zhang & V Ng (eds), Proceedings of the 8th SIGHAN Workshop on Chinese Language Processing, SIGHAN 2015 - co-located with 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing, ACL IJCNLP 2015. Proceedings of the 8th SIGHAN Workshop on Chinese Language Processing, SIGHAN 2015 - co-located with 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing, ACL IJCNLP 2015, Association for Computational Linguistics (ACL), pp. 120-127, 8th SIGHAN Workshop on Chinese Language Processing, SIGHAN 2015, Beijing, China, 15/7/30.

Jin G, Kawahara D, Kurohashi S. Chinese semantic role labeling using high-quality syntactic knowledge. In Yu L-C, Sui Z, Zhang Y, Ng V, editors, Proceedings of the 8th SIGHAN Workshop on Chinese Language Processing, SIGHAN 2015 - co-located with 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing, ACL IJCNLP 2015. Association for Computational Linguistics (ACL). 2015. p. 120-127. (Proceedings of the 8th SIGHAN Workshop on Chinese Language Processing, SIGHAN 2015 - co-located with 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing, ACL IJCNLP 2015).

Jin, Gongye ; Kawahara, Daisuke ; Kurohashi, Sadao. / Chinese semantic role labeling using high-quality syntactic knowledge. Proceedings of the 8th SIGHAN Workshop on Chinese Language Processing, SIGHAN 2015 - co-located with 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing, ACL IJCNLP 2015. editor / Liang-Chih Yu ; Zhifang Sui ; Yue Zhang ; Vincent Ng. Association for Computational Linguistics (ACL), 2015. pp. 120-127 (Proceedings of the 8th SIGHAN Workshop on Chinese Language Processing, SIGHAN 2015 - co-located with 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing, ACL IJCNLP 2015).

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abstract = "This paper presents an application of Chinese syntactic knowledge for semantic role labeling (SRL). Besides basic morphological information, syntactic structures are crucial in SRL. However, it is difficult to learn such information from limited, small-scale, manually annotated training data. Instead of manually increasing the size of annotated data, we use a large amount of automatically extracted syntactic knowledge to improve the performance of SRL.",

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Chinese semantic role labeling using high-quality syntactic knowledge

Abstract

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Conference

ASJC Scopus subject areas

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