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Linguistic theory based contextual evidence mining for statistical Chinese co-reference resolution
Zhao, Jun; Liu, Fei-Fan
2007-07-01
发表期刊JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY
卷号22期号:4页码:608-617
文章类型Article
摘要Under statistical learning framework, the paper focuses on how to use traditional linguistic findings on anaphora resolution as a guide for mining and organizing contextual features for Chinese co-reference resolution. The main achievements are as follows. (1) In order to simulate '' syntactic and semantic parallelism factor '', we extract '' bags of word form and POS '' feature and '' bag of semes '' feature from the contexts of the entity mentions and incorporate them into the baseline feature set. (2) Because it is too coarse to use the feature of bags of word form, POS tag and seme to determine the syntactic and semantic parallelism between two entity mentions, we propose a method for contextual feature reconstruction based on semantic similarity computation, in order that the reconstructed contextual features could better approximate the anaphora resolution factor of '' Syntactic and Semantic Parallelism Preferences ''. (3) We use an entity-mention-based contextual feature representation instead of isolated word-based contextual feature representation, and expand the size of the contextual windows in addition, in order to approximately simulate '' the selectional restriction factor '' for anaphora resolution. The experiments show that the multi-level contextual features are useful for co-reference resolution, and the statistical system incorporated with these features performs well on the standard ACE datasets.
关键词Natural Language Processing Information Extraction Co-reference Resolution Anaphora Resolution
WOS标题词Science & Technology ; Technology
关键词[WOS]COREFERENCE
收录类别SCI
语种英语
WOS研究方向Computer Science
WOS类目Computer Science, Hardware & Architecture ; Computer Science, Software Engineering
WOS记录号WOS:000248356900015
引用统计
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/9447
专题09年以前成果
作者单位Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100080, Peoples R China
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Zhao, Jun,Liu, Fei-Fan. Linguistic theory based contextual evidence mining for statistical Chinese co-reference resolution[J]. JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY,2007,22(4):608-617.
APA Zhao, Jun,&Liu, Fei-Fan.(2007).Linguistic theory based contextual evidence mining for statistical Chinese co-reference resolution.JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY,22(4),608-617.
MLA Zhao, Jun,et al."Linguistic theory based contextual evidence mining for statistical Chinese co-reference resolution".JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY 22.4(2007):608-617.
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