Improving nominal SRL in Chinese language with verbal SRL information and automatic predicate recognition

36Citations
Citations of this article
83Readers
Mendeley users who have this article in their library.

Abstract

This paper explores Chinese semantic role labeling (SRL) for nominal predicates. Besides those widely used features in verbal SRL, various nominal SRL-specific features are first included. Then, we improve the performance of nominal SRL by integrating useful features derived from a state-of-the-art verbal SRL system. Finally, we address the issue of automatic predicate recognition, which is essential for a nominal SRL system. Evaluation on Chinese NomBank shows that our research in integrating various features derived from verbal SRL significantly improves the performance. It also shows that our nominal SRL system much outperforms the state-of-the-art ones. © 2009 ACL and AFNLP.

Cited by Powered by Scopus

Semantic role labeling

153Citations
68Readers
Get full text

A hybrid model for Chinese Spelling check

24Citations
30Readers
Get full text

Topic-driven multi-document summarization

19Citations
16Readers
Get full text

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Li, J., Zhou, G., Zhao, H., Zhu, Q., & Qian, P. (2009). Improving nominal SRL in Chinese language with verbal SRL information and automatic predicate recognition. In EMNLP 2009 - Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: A Meeting of SIGDAT, a Special Interest Group of ACL, Held in Conjunction with ACL-IJCNLP 2009 (pp. 1280–1288). Association for Computational Linguistics (ACL). https://doi.org/10.3115/1699648.1699674

Readers over time

‘09‘10‘11‘12‘13‘14‘15‘16‘17‘19‘20‘21‘22‘23‘24‘2506121824

Readers' Seniority

Tooltip

PhD / Post grad / Masters / Doc 30

68%

Researcher 8

18%

Professor / Associate Prof. 4

9%

Lecturer / Post doc 2

5%

Readers' Discipline

Tooltip

Computer Science 39

81%

Linguistics 6

13%

Engineering 2

4%

Neuroscience 1

2%

Save time finding and organizing research with Mendeley

Sign up for free
0