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中文摘要：
依存句法是句法分析的一种，相比于短语结构句法分析，依存句法具有更简洁的表达方式。该文采用英文语义角色标注的研究方法，实现了一个基于中文依存句法分析的语义角色标注系统。该系统针对中文依存关系树，采用有效的剪枝算法和特征，使用最大熵分类器进行语义角色的识别和分类。系统使用了两种不同的语料，一种是由标准短语结构句法分析（CTB5．0）转换而来，另一种是CoNLL2009公布的中文语料。系统分别在两种语料的标准谓词和自动谓词的基础上进行实验，在标准谓词上取得的F1值分别为84．30％和81．68％，在自动谓词上的F1值为81．02％和81．33％。
英文摘要：
Dependency representations are more simple and intuitive than constituent representations for Chinese parse. This paper implements a Chinese dependency parse based semantic role labeling （SRL） by using the similar methods in English SRL. In the system, effective pruning algorithm and useful features are adopted for Chinese de- pendency tree, and the semantic role identification and classification are accomplished by a maximum entropy classifi- er. Two different corpora are adopted to test our system, one is transferred from constituent-based corpus （CTBS. 0）, and the other is Chinese dataset provided by CoNLL 2009 shared task. Based on the two datasets, the system achieves, respectively, 84.3% and 81.68% in labeled F1 for gold predicates, and 81.02% and 81. 33% for automatic predicates.
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