The aim of the CASE 2021 Shared Task 1 (H\"urriyeto\u{g}lu et al., 2021) was to detect and classify socio-political and crisis event information at document, sentence, cross-sentence, and token levels in a multilingual setting, with each of these subtasks being evaluated separately in each test language. Our submission contained entries in all of the subtasks, and the scores obtained validated our research finding: That the multilingual aspect of the tasks should be embraced, so that modeling and training regimes use the multilingual nature of the tasks to their mutual benefit, rather than trying to tackle the different languages separately. Our code is available at https://github.com/HandshakesByDC/case2021/
@article{arxiv.2110.15599,
title = {Handshakes AI Research at CASE 2021 Task 1: Exploring different approaches for multilingual tasks},
author = {Vivek Kalyan and Paul Tan and Shaun Tan and Martin Andrews},
journal= {arXiv preprint arXiv:2110.15599},
year = {2021}
}
Comments
Accepted paper for CASE 2021 workshop at ACL-IJCNLP 2021. (6 pages including references)