Treasures Outside Contexts: Improving Event Detection via Global Statistics

Rui Li, Wenlin Zhao, Cheng Yang, Sen Su


Abstract
Event detection (ED) aims at identifying event instances of specified types in given texts, which has been formalized as a sequence labeling task. As far as we know, existing neural-based ED models make decisions relying entirely on the contextual semantic features of each word in the inputted text, which we find is easy to be confused by the varied contexts in the test stage. To this end, we come up with the idea of introducing a set of statistical features from word-event co-occurrence frequencies in the entire training set to cooperate with contextual features. Specifically, we propose a Semantic and Statistic-Joint Discriminative Network (SS-JDN) consisting of a semantic feature extractor, a statistical feature extractor, and a joint event discriminator. In experiments, SS-JDN effectively exceeds ten recent strong baselines on ACE2005 and KBP2015 datasets. Further, we perform extensive experiments to comprehensively probe SS-JDN.
Anthology ID:
2021.emnlp-main.206
Volume:
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
Month:
November
Year:
2021
Address:
Online and Punta Cana, Dominican Republic
Editors:
Marie-Francine Moens, Xuanjing Huang, Lucia Specia, Scott Wen-tau Yih
Venue:
EMNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
2625–2635
Language:
URL:
https://aclanthology.org/2021.emnlp-main.206
DOI:
10.18653/v1/2021.emnlp-main.206
Bibkey:
Cite (ACL):
Rui Li, Wenlin Zhao, Cheng Yang, and Sen Su. 2021. Treasures Outside Contexts: Improving Event Detection via Global Statistics. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pages 2625–2635, Online and Punta Cana, Dominican Republic. Association for Computational Linguistics.
Cite (Informal):
Treasures Outside Contexts: Improving Event Detection via Global Statistics (Li et al., EMNLP 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.emnlp-main.206.pdf
Video:
 https://aclanthology.org/2021.emnlp-main.206.mp4
Code
 buted/ssjdn