CASIA OpenIR  > 模式识别国家重点实验室  > 自然语言处理
陈玉博1; 何世柱1; 刘康1; 赵军1; 吕学强2
Source Publication中文信息学报
Other Abstract
Named entity disambiguation is one of the key techniques in naturallanguage processing. lt aims at resolving
the name ambiguity problem which is common in the textual information and plays an important role in many
different areas , such as information retrieval , knowledge engineering and semantic web. Entity linking is an impor
tant method of entity disambiguation , which aims to map an entity to an entry stored in the existing knowledge base.
Several methods have been proposed to tackle this probl em , but they a re largely based on the co-occurrence statistics
of terms between the text around the entity mention and the document associated with the entity. It can't capture va
rious semantic relations. To capture more semantic relations , in this paper we make use of multiple features. To
make the best use of the features , we propose a learning to rank algorithm for entity linking. lt effectively utilizes
the relationship information among the candidates and save a lot of time and effort. The experiment results on the
T AC KBP 2009 dataset demonstrate the effectiveness of our proposed features and framework. The accuracy on the
dataset is 84.38% , exceeding the best result of the TAC KBP 2009 by 2. 21%.
Keyword实体消歧 实体链接 排序学习
Document Type期刊论文
Corresponding Author刘康
First Author AffilicationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Corresponding Author AffilicationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
陈玉博,何世柱,刘康,等. 融合多种特征的实体链接技术研究[J]. 中文信息学报,2016,30(4):176-183.
APA 陈玉博,何世柱,刘康,赵军,&吕学强.(2016).融合多种特征的实体链接技术研究.中文信息学报,30(4),176-183.
MLA 陈玉博,et al."融合多种特征的实体链接技术研究".中文信息学报 30.4(2016):176-183.
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