BOOTSTRAPPING FOR EXTRACTING RELATIONS FROM LARGE CORPORA

被引：5

作者：

Li Weigang Liu Ting Li Sheng Information Retrieval Laboratory School of Computer Science and Technology Harbin Institute of Technology Harbin China ^{[150001
]}

机构：

来源：

Journal of Electronics(China) | 2008年 / 01期

关键词：

Relation extraction; Bootstrapping; Patterns; Tuples;

D O I：

暂无

中图分类号：

TP311.5 [软件工程];

学科分类号：

081202 ; 0835 ;

摘要：

A new approach of relation extraction is described in this paper. It adopts a bootstrap- ping model with a novel iteration strategy, which generates more precise examples of specific relation. Compared with previous methods, the proposed method has three main advantages: first, it needs less manual intervention; second, more abundant and reasonable information are introduced to represent a relation pattern; third, it reduces the risk of circular dependency occurrence in bootstrapping. Scalable evaluation methodology and metrics are developed for our task with comparable techniques over TianWang 100G corpus. The experimental results show that it can get 90% precision and have excellent expansibility.

引用

页码：89 / 96

页数：8