Bootstrapped Text-level Named Entity Recognition for Literature

被引：0
|
作者：
Brooke, Julian [1 ]
Baldwin, Timothy [1 ]
Hammond, Adam [2 ]
机构：
[1] Univ Melbourne, Comp & Informat Syst, Melbourne, Vic, Australia
[2] San Diego State Univ, English & Comparat Literature, San Diego, CA 92182 USA
来源：
PROCEEDINGS OF THE 54TH ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS (ACL 2016), VOL 2 | 2016年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
We present a named entity recognition (NER) system for tagging fiction: LitNER. Relative to more traditional approaches, LitNER has two important properties: (1) it makes no use of handtagged data or gazetteers, instead it bootstraps a model from term clusters; and (2) it leverages multiple instances of the same name in a text. Our experiments show it to substantially outperform off-the-shelf supervised NER systems.
引用
收藏
页码：344 / 350
页数：7
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