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基于北京大学中文网库的语义角色分类
引用本文:杨敏,常宝宝.基于北京大学中文网库的语义角色分类[J].中文信息学报,2011,25(2):3-9.
作者姓名:杨敏  常宝宝
作者单位:北京大学 计算语言所,北京 100871;
北京大学 计算语言学教育部重点实验室,北京 100871
基金项目:国家自然科学基金资助项目,社会科学基金资助项目
摘    要:语义角色标注的研究方法中使用最频繁的一类是基于特征工程,将任务转化成分类问题使用机器学习的方法来解决,几乎所有的有指导语义角色标注采用的标注语料都是宾州大学命题库标注体系。近年来,北京大学开发出一套新的标注语料—北京大学中文网库,该文的目的在于测试这类研究方法在新语料的效果,验证之前所使用的特征是否对标注语料具有依赖性。通过实验发现前人方法中的一些不足,尤其个别特征在北大网库上作用更关键。

关 键 词:语义角色标注  北京大学中文网库  序列标注  

Semantic Role Classification Based on Peking University Chinese NetBank
YANG Min,CHANG Baobao.Semantic Role Classification Based on Peking University Chinese NetBank[J].Journal of Chinese Information Processing,2011,25(2):3-9.
Authors:YANG Min  CHANG Baobao
Affiliation:Institute of Computational Linguistics, Peking University, Beijing 100871, China;
Key Laboratory of Computational Linguistics,Ministry of Education, Beijing 100871, China
Abstract:Among all the researches on semantic role labeling(SRL), one important method which has been carried out by many researchers is to convert the task into a classification problem by selecting features, and thenapplying different kinds of classifiers .While almost all the researches based on this kind of supervised learning have been done on the same corpus-Penn Proposition Bank, here we test the same method on a new corpus—Peking University Chinese NetBank, with the goal to figure out whether the wildly used features have a strong dependence on corpus. The experiments have shown that the method and the features have good performance on the new corpus . And compared to the PropBank, some features play crucial roles in classification on the new corpus.
Key wordssemantic role labeling; Peking University Chinese NetBank; sequence labeling
Keywords:semantic role labeling  Peking University Chinese NetBank  sequence labeling  
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