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| 中文名词性谓词语义角色标注 |
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李军辉1,2, 周国栋1,2, 朱巧明1,2, 钱培德1,2
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1.苏州大学 计算机科学与技术学院,江苏 苏州 215006;2.江苏省计算机信息处理技术重点实验室,江苏 苏州 215006
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| 摘要: |
| 研究了中文名词性谓词的语义角色标注(semantic role labeling,简称SRL).在使用传统动词性谓词SRL 相关特征的基础上,进一步提出了名词性谓词SRL 相关的特征集.此外,探索了中文动词性谓词SRL 对中文名词性谓词SRL 的影响,并且联合谓词自动识别实现了全自动的中文名词性谓词SRL.在中文NomBank 上的实验结果表明,中文动词性谓词的SRL 合理使用能够大幅度提高中文名词性谓词的SRL 性能;基于正确句法树和正确谓词识别,中文名词性谓词的SRL 性能F1 值达到了72.67,大大优于目前国内外的同类系统;基于自动句法树和自动谓词识别,性能F1 值为55.14. |
| 关键词: 语义角色标注 名词性谓词相关特征 动词性语义角色标注特征 名词性谓词识别 |
| DOI：10.3724/SP.J.1001.2011.03885 |
| 分类号: |
| 基金项目:国家自然科学基金(90920004, 60873150, 60970056); 江苏省自然科学基金(BK2008160) |
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| Semantic Role Labeling in Chinese Language for Nominal Predicates |
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LI Jun-Hui1,2, ZHOU Guo-Dong1,2, ZHU Qiao-Ming1,2, QIAN Pei-De1,2
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1.School of Computer Science and Technology, Soochow University, Suzhou 215006, China;2.Jiangsu Provincial Key Laboratory for Computer Information Processing Technology, Suzhou 215006, China
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| Abstract: |
| This paper explores semantic role labeling (SRL) in the Chinese language for nominal predicates. In addition to the widely adopted features of verbal SRL, various nominal predicate-specific features are also explored. Moreover, the nominal SRL performance has been improved by properly integrating features that were derived from a state-of-the-art verbal SRL system. Finally, the paper explains in detail the nominal predicate recognition, which is essential in a fully automatic nominal SRL system. Evaluations on Chinese NomBank show that proper integration of a verbal SRL system significantly improves the performance of a nominal SRL. It also shows that this nominal SRL system achieves the performance of 72.67 in F1-measure on golden parse trees and golden predicates, and outperforms the state-of-the-art nominal SRL systems in the Chinese language; however, the performance drops to 55.14 in F1-measure on automatic parse trees and automatic predicates. |
| Key words: semantic role labeling nominal predicate-specific feature verbal SRL feature nominal predicate recognition |
