PESE: Event Structure Extraction using Pointer Network based Encoder-Decoder Architecture

Alapan Kuila, Sudeshna Sarkar

Abstract
The task of event extraction (EE) aims to find the events and event-related argument information from the text and represent them in a structured format. Most previous works try to solve the problem by separately identifying multiple substructures and aggregating them to get the complete event structure. The problem with the methods is that it fails to identify all the interdependencies among the event participants (event-triggers, arguments, and roles). In this paper, we represent each event record in a unique tuple format that contains trigger phrase, trigger type, argument phrase, and corresponding role information. Our proposed pointer network-based encoder-decoder model generates an event tuple in each time step by exploiting the interactions among event participants and presenting a truly end-to-end solution to the EE task. We evaluate our model on the ACE2005 dataset, and experimental results demonstrate the effectiveness of our model by achieving competitive performance compared to the state-of-the-art methods.
Anthology ID:
2022.aacl-main.80
Volume:
Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)
Month:
November
Year:
2022
Address:
Online only
Editors:
Yulan He, Heng Ji, Sujian Li, Yang Liu, Chua-Hui Chang
Venues:
AACL | IJCNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
1091–1100
Language:
URL:
https://aclanthology.org/2022.aacl-main.80
DOI:
10.18653/v1/2022.aacl-main.80
Bibkey:
Cite (ACL):
Alapan Kuila and Sudeshna Sarkar. 2022. PESE: Event Structure Extraction using Pointer Network based Encoder-Decoder Architecture. In Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pages 1091–1100, Online only. Association for Computational Linguistics.
Cite (Informal):
PESE: Event Structure Extraction using Pointer Network based Encoder-Decoder Architecture (Kuila & Sarkar, AACL-IJCNLP 2022)
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PDF:
https://preview.aclanthology.org/dois-2013-emnlp/2022.aacl-main.80.pdf
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