OneEE: A One-Stage Framework for Fast Overlapping and Nested Event Extraction

Hu Cao, Jingye Li, Fangfang Su, Fei Li, Hao Fei, Shengqiong Wu, Bobo Li, Liang Zhao, Donghong Ji


Abstract
Event extraction (EE) is an essential task of information extraction, which aims to extract structured event information from unstructured text. Most prior work focuses on extracting flat events while neglecting overlapped or nested ones. A few models for overlapped and nested EE includes several successive stages to extract event triggers and arguments,which suffer from error propagation. Therefore, we design a simple yet effective tagging scheme and model to formulate EE as word-word relation recognition, called OneEE. The relations between trigger or argument words are simultaneously recognized in one stage with parallel grid tagging, thus yielding a very fast event extraction speed. The model is equipped with an adaptive event fusion module to generate event-aware representations and a distance-aware predictor to integrate relative distance information for word-word relation recognition, which are empirically demonstrated to be effective mechanisms. Experiments on 3 overlapped and nested EE benchmarks, namely FewFC, Genia11, and Genia13, show that OneEE achieves the state-of-the-art (SOTA) results. Moreover, the inference speed of OneEE is faster than those of baselines in the same condition, and can be further substantially improved since it supports parallel inference.
Anthology ID:
2022.coling-1.170
Volume:
Proceedings of the 29th International Conference on Computational Linguistics
Month:
October
Year:
2022
Address:
Gyeongju, Republic of Korea
Venue:
COLING
SIG:
Publisher:
International Committee on Computational Linguistics
Note:
Pages:
1953–1964
Language:
URL:
https://aclanthology.org/2022.coling-1.170
DOI:
Bibkey:
Cite (ACL):
Hu Cao, Jingye Li, Fangfang Su, Fei Li, Hao Fei, Shengqiong Wu, Bobo Li, Liang Zhao, and Donghong Ji. 2022. OneEE: A One-Stage Framework for Fast Overlapping and Nested Event Extraction. In Proceedings of the 29th International Conference on Computational Linguistics, pages 1953–1964, Gyeongju, Republic of Korea. International Committee on Computational Linguistics.
Cite (Informal):
OneEE: A One-Stage Framework for Fast Overlapping and Nested Event Extraction (Cao et al., COLING 2022)
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PDF:
https://aclanthology.org/2022.coling-1.170.pdf
Code
 cao-hu/oneee