TextEE: Benchmark, Reevaluation, Reflections, and Future Challenges in Event Extraction

Kuan-Hao Huang, I-Hung Hsu, Tanmay Parekh, Zhiyu Xie, Zixuan Zhang, Prem Natarajan, Kai-Wei Chang, Nanyun Peng, Heng Ji


Abstract
Event extraction has gained considerable interest due to its wide-ranging applications. However, recent studies draw attention to evaluation issues, suggesting that reported scores may not accurately reflect the true performance. In this work, we identify and address evaluation challenges, including inconsistency due to varying data assumptions or preprocessing steps, the insufficiency of current evaluation frameworks that may introduce dataset or data split bias, and the low reproducibility of some previous approaches. To address these challenges, we present TextEE, a standardized, fair, and reproducible benchmark for event extraction. TextEE comprises standardized data preprocessing scripts and splits for 16 datasets spanning eight diverse domains and includes 14 recent methodologies, conducting a comprehensive benchmark reevaluation. We also evaluate five varied large language models on our TextEE benchmark and demonstrate how they struggle to achieve satisfactory performance. Inspired by our reevaluation results and findings, we discuss the role of event extraction in the current NLP era, as well as future challenges and insights derived from TextEE. We believe TextEE, the first standardized comprehensive benchmarking tool, will significantly facilitate future event extraction research.
Anthology ID:
2024.findings-acl.760
Volume:
Findings of the Association for Computational Linguistics: ACL 2024
Month:
August
Year:
2024
Address:
Bangkok, Thailand
Editors:
Lun-Wei Ku, Andre Martins, Vivek Srikumar
Venue:
Findings
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
12804–12825
Language:
URL:
https://aclanthology.org/2024.findings-acl.760
DOI:
10.18653/v1/2024.findings-acl.760
Bibkey:
Cite (ACL):
Kuan-Hao Huang, I-Hung Hsu, Tanmay Parekh, Zhiyu Xie, Zixuan Zhang, Prem Natarajan, Kai-Wei Chang, Nanyun Peng, and Heng Ji. 2024. TextEE: Benchmark, Reevaluation, Reflections, and Future Challenges in Event Extraction. In Findings of the Association for Computational Linguistics: ACL 2024, pages 12804–12825, Bangkok, Thailand. Association for Computational Linguistics.
Cite (Informal):
TextEE: Benchmark, Reevaluation, Reflections, and Future Challenges in Event Extraction (Huang et al., Findings 2024)
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PDF:
https://preview.aclanthology.org/autopr/2024.findings-acl.760.pdf