DAAI at CASE 2021 Task 1: Transformer-based Multilingual Socio-political and Crisis Event Detection

Hettiarachchi, Hansi and Adedoyin-Olowe, Mariam and Bhogal, Jagdev and Gaber, Mohamed Medhat (2021) DAAI at CASE 2021 Task 1: Transformer-based Multilingual Socio-political and Crisis Event Detection. In: 4th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE 2021), 1st August 2021, Online.

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Abstract

Automatic socio-political and crisis event detection has been a challenge for natural language processing as well as social and political science communities, due to the diversity and nuance in such events and high accuracy requirements. In this paper, we propose an approach which can handle both document and cross-sentence level event detection in a multilingual setting using pretrained transformer models. Our approach became the winning solution in document level predictions and secured the 3rd place in cross-sentence level predictions for the English language. We could also achieve competitive results for other languages to prove the effectiveness and universality of our approach.

Item Type: Conference or Workshop Item (Paper)
Identification Number: https://doi.org/10.18653/v1/2021.case-1.16
Dates:
DateEvent
31 May 2021Accepted
6 August 2021Published
Subjects: CAH11 - computing > CAH11-01 - computing > CAH11-01-01 - computer science
Divisions: Faculty of Computing, Engineering and the Built Environment > School of Computing and Digital Technology
Depositing User: Hansi Hettiarachchi
Date Deposited: 21 Dec 2021 16:01
Last Modified: 21 Dec 2021 16:01
URI: http://www.open-access.bcu.ac.uk/id/eprint/12549

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