本周五(12月19日)下午4:10pm学术报告-Encoding Relation Requirements for Relation Extraction via Joint Inference

作者: 分类: 学术报告 时间: 2014-12-19 评论: 暂无评论

报告题目:Encoding Relation Requirements for Relation Extraction via
Joint Inference - 2014年ACL论文

报告摘要: Most existing relation extraction models make predictions for
each entity pair locally and individually, while ignoring implicit
global clues available in the knowledge base, sometimes leading to
conflicts among local predictions from different entity pairs. We
therefore propose a joint inference framework that utilizes these global
clues to resolve disagreements among local predictions. We exploit two
kinds of clues to generate constraints which can capture the implicit
type and cardinality requirements of a relation. Experimental results on
three datasets, in both English and Chinese, show that our framework
outperforms the state-of-the-art relation extraction models when such
clues are applicable to the datasets. And, we find that the clues learnt
automatically from existing knowledge bases perform comparably to those
refined by human.

讲者介绍:Dr. Yansong Feng a Lecturer (Assistant Professor) in the
Institute of Computer Science and Technology at Peking University,
working with the group of Web Information Processing. Before that, he
worked with Prof. Mirella Lapata and obtained my PhD from the School of
Informatics at the University of Edinburgh.

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