Harnessing Open Information Extraction for Entity Classification in a French Corpus

被引:4
作者
Gotti, Fabrizio [1 ]
Langlais, Philippe [1 ]
机构
[1] Univ Montreal, RALI, CP 6128 Succursale Ctr Ville, Montreal, PQ H3C 3J7, Canada
来源
ADVANCES IN ARTIFICIAL INTELLIGENCE, AI 2016 | 2016年 / 9673卷
关键词
Natural language processing; Open information extraction; Named entities; Entity classification; KNOWLEDGE-BASE; SCALE;
D O I
10.1007/978-3-319-34111-8_20
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
We describe a recall-oriented open information extraction system designed to extract knowledge from French corpora. We put it to the test by showing that general domain information triples (extracted from French Wikipedia) can be used for deriving new knowledge from domain-specific documents unrelated to Wikipedia. Specifically, we can label entity instances extracted in one corpus with the entity types identified in the other, with little supervision. We believe that the present study is the first one that focusses on such a cross-domain, recall-oriented approach in open information extraction.
引用
收藏
页码:150 / 161
页数:12
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