5ZN-3 Duality based Expansion for Relation of Entity Pair

概要

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Traditional relation extraction requires pre-defined relations and many human annotated training data. Open relation extraction demands a set of heuristic rules to extract all potential relations from text. These requirements reduce the practicability and robustness of information extraction system. In this paper, we propose a Relation Expansion framework, which uses a few seed sentences marked up with two entities to expand a ranked list of sentences containing target relation between entity pair. The proposed framework uses dual expansion model to incrementally discover relevant sentences. Then these extracted relation instances are ranked according their relevance to the given seeds. The proposed framework is tested with four frequently used relationships; the results show the effectiveness of relation expansion framework.
一般社団法人情報処理学会の論文
2010-03-08