The Dots Have Their Values: Exploiting the Node-Edge Connections in Graph-based Neural Models for Document-level Relation Extraction

Hieu Minh Tran, Minh Trung Nguyen, Thien Huu Nguyen

Abstract
The goal of Document-level Relation Extraction (DRE) is to recognize the relations between entity mentions that can span beyond sentence boundary. The current state-of-the-art method for this problem has involved the graph-based edge-oriented model where the entity mentions, entities, and sentences in the documents are used as the nodes of the document graphs for representation learning. However, this model does not capture the representations for the nodes in the graphs, thus preventing it from effectively encoding the specific and relevant information of the nodes for DRE. To address this issue, we propose to explicitly compute the representations for the nodes in the graph-based edge-oriented model for DRE. These node representations allow us to introduce two novel representation regularization mechanisms to improve the representation vectors for DRE. The experiments show that our model achieves state-of-the-art performance on two benchmark datasets.
Anthology ID:
2020.findings-emnlp.409
Volume:
Findings of the Association for Computational Linguistics: EMNLP 2020
Month:
November
Year:
2020
Address:
Online
Editors:
Trevor Cohn, Yulan He, Yang Liu
Venue:
Findings
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
4561–4567
Language:
URL:
https://aclanthology.org/2020.findings-emnlp.409
DOI:
10.18653/v1/2020.findings-emnlp.409
Bibkey:
Cite (ACL):
Hieu Minh Tran, Minh Trung Nguyen, and Thien Huu Nguyen. 2020. The Dots Have Their Values: Exploiting the Node-Edge Connections in Graph-based Neural Models for Document-level Relation Extraction. In Findings of the Association for Computational Linguistics: EMNLP 2020, pages 4561–4567, Online. Association for Computational Linguistics.
Cite (Informal):
The Dots Have Their Values: Exploiting the Node-Edge Connections in Graph-based Neural Models for Document-level Relation Extraction (Minh Tran et al., Findings 2020)
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https://preview.aclanthology.org/nschneid-patch-5/2020.findings-emnlp.409.pdf
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