Tagging complex NEs with MaxEnt models: Layered structures versus extended tagset

	Tagging complex NEs with MaxEnt models: Layered structures versus extended tagset
	Xiong, DY ; Yu, HK ; Liu, Q
	2005
发表期刊	NATURAL LANGUAGE PROCESSING - IJCNLP 2004
ISSN	0302-9743
卷号	3248 页码:537-544
摘要	The paper discusses two policies for recognizing NEs with complex structures by maximum entropy models. One policy is to develop cascaded MaxEnt models at different levels. The other is to design more detailed tags with human knowledge in order to represent complex structures. The experiments on Chinese organization names recognition indicate that layered structures result in more accurate models while extended tags can not lead to positive results as expected. We empirically prove that the {start, continue, end, unique, other} tag set is the best tag set for NE recognition with MaxEnt models.
收录类别	SCI
语种	英语
WOS研究方向	Computer Science
WOS类目	Computer Science, Artificial Intelligence
WOS记录号	WOS:000228359800057
出版者	SPRINGER-VERLAG BERLIN
引用统计	被引频次：1[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/10121
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Xiong, DY
作者单位	1.Chinese Acad Sci, Comp Technol Inst, Beijing, Peoples R China 2.Chinese Acad Sci, Grad Sch, Beijing, Peoples R China 3.Peking Univ, Inst Computat Linguistics, Beijing 100871, Peoples R China 4.Beijing Univ Chem Technol, Coll Informat Sci & Technol, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Xiong, DY,Yu, HK,Liu, Q. Tagging complex NEs with MaxEnt models: Layered structures versus extended tagset[J]. NATURAL LANGUAGE PROCESSING - IJCNLP 2004,2005,3248:537-544.
APA	Xiong, DY,Yu, HK,&Liu, Q.(2005).Tagging complex NEs with MaxEnt models: Layered structures versus extended tagset.NATURAL LANGUAGE PROCESSING - IJCNLP 2004,3248,537-544.
MLA	Xiong, DY,et al."Tagging complex NEs with MaxEnt models: Layered structures versus extended tagset".NATURAL LANGUAGE PROCESSING - IJCNLP 2004 3248(2005):537-544.