SU-NLP at CASE 2021 Task 1: Protest News Detection for English

Furkan Çelik, Tuğberk Dalkılıç, Fatih Beyhan, Reyyan Yeniterzi


Abstract
This paper summarizes our group’s efforts in the multilingual protest news detection shared task, which is organized as a part of the Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE) Workshop. We participated in all four subtasks in English. Especially in the identification of event containing sentences task, our proposed ensemble approach using RoBERTa and multichannel CNN-LexStem model yields higher performance. Similarly in the event extraction task, our transformer-LSTM-CRF architecture outperforms regular transformers significantly.
Anthology ID:
2021.case-1.17
Volume:
Proceedings of the 4th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE 2021)
Month:
August
Year:
2021
Address:
Online
Venues:
ACL | CASE | IJCNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
131–137
Language:
URL:
https://aclanthology.org/2021.case-1.17
DOI:
10.18653/v1/2021.case-1.17
Bibkey:
Cite (ACL):
Furkan Çelik, Tuğberk Dalkılıç, Fatih Beyhan, and Reyyan Yeniterzi. 2021. SU-NLP at CASE 2021 Task 1: Protest News Detection for English. In Proceedings of the 4th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE 2021), pages 131–137, Online. Association for Computational Linguistics.
Cite (Informal):
SU-NLP at CASE 2021 Task 1: Protest News Detection for English (Çelik et al., CASE 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.case-1.17.pdf