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| 基于依存特征的汉语框架语义角色自动标注 | |
| 引用本文： | 王智强,李茹,阴志洲,刘海静,李双红. 基于依存特征的汉语框架语义角色自动标注[J]. 中文信息学报, 2013, 27(2): 34-41 |
| 作者姓名： | 王智强 李茹 阴志洲 刘海静 李双红 |
| 作者单位： | 1. 山西大学 计算机与信息技术学院,山西 太原 030006; 2. 计算智能与中文信息处理教育部重点实验室,山西 太原 030006; 3. School of Information Technologies, University of Sydney |
| 基金项目： | 国家自然科学基金资助项目，国家语委"十二五"科研规划资助项目，国家863高技术研究发展计划资助项目，山西省国际科技合作资助项目，山西省实验室开放基金资助项目 |
| 摘 要： | 语义角色标注是浅层语义分析的一种实现方式。目前汉语框架语义角色自动标注一般被看作以词为基本标注单元的序列标注问题,而已有研究中仅在词、词性层面来选取特征,标注结果并不理想。该文利用树条件随机场模型,通过在词、词性层面特征的基础上依次加入不同类型的依存特征,研究依存特征对汉语框架语义角色标注的影响。实验设置了8类,共24种特征模板,结果显示,加入依序特征的最优模版使标注结果的F值提高近3%,特别是对较长框架语义角色的标注结果有较好的改善。 |
| 关 键 词： | 框架语义角色 依存特征 T-CRF模型 |
Automatic Labeling of Chinese Frame Semantic Roles Based on Dependency Features |
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| WANG Zhiqiang , LI Ru , YIN Zhizhou , LIU Haijing , LI Shuanghong. Automatic Labeling of Chinese Frame Semantic Roles Based on Dependency Features[J]. Journal of Chinese Information Processing, 2013, 27(2): 34-41 | |
| Authors: | WANG Zhiqiang LI Ru YIN Zhizhou LIU Haijing LI Shuanghong |
| Affiliation: | 1. School of Computer & Information Technology, Shanxi University, Taiyuan, Shanxi 030006,China; 2. Key Laboratory of Ministry of Education for Computation Intelligence & Chinese Information Processing, Taiyuan, Shanxi 030006, China; 3. School of Information Technologies, University of Sydney, Australia |
| Abstract: | Semantic roles labeling is a kind of the shallow semantic analysis. Currently, Chinese frame semantic roles labeling is generally viewed as sequence labeling task based on the basic tagging unit of words. The current work is defected in only word or POS information considered. This paper studies the impact of the dependency features on the semantic roles labeling under the T-CRF model, integrating the dependency features among the words in the dependency syntax with the word and POS information. The experiment with 24 feature templates in 8 categories shows that the F-measure of the best templates is improved by 3%. Especially, the results on the long frame semantic roles are improved more significantly. Key wordsframe semantic roles;dependency features;T-CRF model |
| Keywords: | frame semantic roles dependency features T-CRF model |
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