Relation Extraction among Multiple Entities Using a Dual Pointer Network with a Multi-Head Attention Mechanism
Seongsik Park, Harksoo Kim · 2019
Many previous studies on relation extraction have been focused on finding only one relation between two entities in a single sentence.However, we can easily find the fact that multiple entities exist in a single sentence and the entities form multiple relations.To resolve this problem, we propose a relation extraction model based on a dual pointer network with a multi-head attention mechanism.The proposed model finds n-to-1 subject-object relations by using a forward decoder called an object decoder.Then, it finds 1-to-n subject-object relations by using a backward decoder called a subject decoder.In the experiments with the ACE-05 dataset and the NYT dataset, the proposed model achieved the state-of-the-art performances (F1-score of 80.5% in the ACE-05 dataset, F1-score of 78.3% in the NYT dataset)