Title
Translation-Based Implicit Annotation Projection for Zero-Shot Cross-Lingual Event Argument Extraction
Abstract
Zero-shot cross-lingual event argument extraction (EAE) is a challenging yet practical problem in Information Extraction. Most previous works heavily rely on external structured linguistic features, which are not easily accessible in real-world scenarios. This paper investigates a translation-based method to implicitly project annotations from the source language to the target language. With the use of translation-based parallel corpora, no additional linguistic features are required during training and inference. As a result, the proposed approach is more cost effective than previous works on zero-shot cross-lingual EAE. Moreover, our implicit annotation projection approach introduces less noises and hence is more effective and robust than explicit ones. Experimental results show that our model achieves the best performance, outperforming a number of competitive baselines. The thorough analysis further demonstrates the effectiveness of our model compared to explicit annotation projection approaches.
Year
DOI
Venue
2022
10.1145/3477495.3531808
SIGIR '22: Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval
Keywords
DocType
Citations 
event extraction, cross-lingual learning, word alignment
Conference
0
PageRank 
References 
Authors
0.34
4
7
Name
Order
Citations
PageRank
Chenwei Lou100.34
Jun Gao200.34
Changlong Yu300.34
Wei Wang46012.81
Huan Zhao500.68
Wei-Wei Tu6337.86
Xu Ruifeng743253.04