Papers › EmRel: Joint Representation of Entities and Embedded Relations for Multi-triple Extraction

EmRel: Joint Representation of Entities and Embedded Relations for Multi-triple Extraction

1 Jul 2022NAACL 2022 7archive 2025-07-28

Benfeng Xu, Quan Wang, Yajuan Lyu, Yabing Shi, Yong Zhu, Jie Gao, Zhendong Mao

Multi-triple extraction is a challenging task due to the existence of informative inter-triple correlations, and consequently rich interactions across the constituent entities and relations.While existing works only explore entity representations, we propose to explicitly introduce relation representation, jointly represent it with entities, and novelly align them to identify valid triples.We perform comprehensive experiments on document-level relation extraction and joint entity and relation extraction along with ablations to demonstrate the advantage of the proposed method.

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Document-level Relation ExtractionJoint Entity and Relation ExtractionRelation Extraction

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