Semantic role tagging for chinese at the lexical level

Oi Yee Kwong; Benjamin K. Tsou

doi:10.1007/11562214_70

Semantic role tagging for chinese at the lexical level

Oi Yee Kwong
, Benjamin K. Tsou

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

1 Citation (Scopus)

Abstract

This paper reports on a study of semantic role tagging in Chinese, in the absence of a parser. We investigated the effect of using only lexical information in statistical training; and proposed to identify the relevant headwords in a sentence as a first step to partially locate the corresponding constituents to be labelled. Experiments were done on a textbook corpus and a news corpus, representing simple data and complex data respectively. Results suggested that in Chinese, simple lexical features are useful enough when constituent boundaries are known, while parse information might be more important for complicated sentences than simple ones. Several ways to improve the headword identification results were suggested, and we also plan to explore some class-based techniques for the task, with reference to existing semantic lexicons. © Springer-Verlag Berlin Heidelberg 2005.

Original language	English
Title of host publication	Natural Language Processing - IJCNLP 2005 - Second International Joint Conference, Proceedings
Publisher	Springer Verlag
Pages	804-814
Volume	3651 LNAI
ISBN (Print)	3540291725, 9783540291725
DOIs	https://doi.org/10.1007/11562214_70
Publication status	Published - 2005
Event	2nd International Joint Conference on Natural Language Processing, IJCNLP 2005 - Jeju Island, Korea, Republic of Duration: 11 Oct 2005 → 13 Oct 2005

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	3651 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	2nd International Joint Conference on Natural Language Processing, IJCNLP 2005
Place	Korea, Republic of
City	Jeju Island
Period	11/10/05 → 13/10/05

Bibliographical note

Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

Funding

This work is supported by Competitive Earmarked Research Grants (CERG) of the Research Grants Council of Hong Kong under grant Nos. CityU1233/01H and CityU1317/03H.

RGC Funding Information

RGC-funded

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10.1007/11562214_70

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Kwong, O. Y., & Tsou, B. K. (2005). Semantic role tagging for chinese at the lexical level. In Natural Language Processing - IJCNLP 2005 - Second International Joint Conference, Proceedings (Vol. 3651 LNAI, pp. 804-814). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3651 LNAI). Springer Verlag. https://doi.org/10.1007/11562214_70

Kwong, Oi Yee ; Tsou, Benjamin K. / Semantic role tagging for chinese at the lexical level. Natural Language Processing - IJCNLP 2005 - Second International Joint Conference, Proceedings. Vol. 3651 LNAI Springer Verlag, 2005. pp. 804-814 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "This paper reports on a study of semantic role tagging in Chinese, in the absence of a parser. We investigated the effect of using only lexical information in statistical training; and proposed to identify the relevant headwords in a sentence as a first step to partially locate the corresponding constituents to be labelled. Experiments were done on a textbook corpus and a news corpus, representing simple data and complex data respectively. Results suggested that in Chinese, simple lexical features are useful enough when constituent boundaries are known, while parse information might be more important for complicated sentences than simple ones. Several ways to improve the headword identification results were suggested, and we also plan to explore some class-based techniques for the task, with reference to existing semantic lexicons. {\textcopyright} Springer-Verlag Berlin Heidelberg 2005.",

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Kwong, OY & Tsou, BK 2005, Semantic role tagging for chinese at the lexical level. in Natural Language Processing - IJCNLP 2005 - Second International Joint Conference, Proceedings. vol. 3651 LNAI, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3651 LNAI, Springer Verlag, pp. 804-814, 2nd International Joint Conference on Natural Language Processing, IJCNLP 2005, Jeju Island, Korea, Republic of, 11/10/05. https://doi.org/10.1007/11562214_70

Semantic role tagging for chinese at the lexical level. / Kwong, Oi Yee; Tsou, Benjamin K.
Natural Language Processing - IJCNLP 2005 - Second International Joint Conference, Proceedings. Vol. 3651 LNAI Springer Verlag, 2005. p. 804-814 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3651 LNAI).

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

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AU - Kwong, Oi Yee

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PY - 2005

Y1 - 2005

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AB - This paper reports on a study of semantic role tagging in Chinese, in the absence of a parser. We investigated the effect of using only lexical information in statistical training; and proposed to identify the relevant headwords in a sentence as a first step to partially locate the corresponding constituents to be labelled. Experiments were done on a textbook corpus and a news corpus, representing simple data and complex data respectively. Results suggested that in Chinese, simple lexical features are useful enough when constituent boundaries are known, while parse information might be more important for complicated sentences than simple ones. Several ways to improve the headword identification results were suggested, and we also plan to explore some class-based techniques for the task, with reference to existing semantic lexicons. © Springer-Verlag Berlin Heidelberg 2005.

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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Kwong OY, Tsou BK. Semantic role tagging for chinese at the lexical level. In Natural Language Processing - IJCNLP 2005 - Second International Joint Conference, Proceedings. Vol. 3651 LNAI. Springer Verlag. 2005. p. 804-814. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/11562214_70

Semantic role tagging for chinese at the lexical level

Abstract

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Bibliographical note

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RGC Funding Information

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