Relation Extraction among Multiple Entities Using a Dual Pointer Network with a Multi-Head Attention Mechanism

WS 2019  ·  Seong Sik Park, Harksoo Kim ·

Many previous studies on relation extrac-tion 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 prob-lem, 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 de-coder called an object decoder. Then, it finds 1-to-n subject-object relations by using a backward decoder called a sub-ject 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)

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Results from the Paper

 Ranked #1 on Relation Extraction on ACE 2005 (Cross Sentence metric)

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Task Dataset Model Metric Name Metric Value Global Rank Benchmark
Relation Extraction ACE 2005 Dual Pointer Network Relation classification F1 80.5 # 2
Cross Sentence No # 1