CASE 2021 Task 2: Zero-Shot Classification of Fine-Grained Sociopolitical Events with Transformer Models

Benjamin J. Radford


Abstract
We introduce a method for the classification of texts into fine-grained categories of sociopolitical events. This particular method is responsive to all three Subtasks of Task 2, Fine-Grained Classification of Socio-Political Events, introduced at the CASE workshop of ACL-IJCNLP 2021. We frame Task 2 as textual entailment: given an input text and a candidate event class (“query”), the model predicts whether the text describes an event of the given type. The model is able to correctly classify in-sample event types with an average F1-score of 0.74 but struggles with some out-of-sample event types. Despite this, the model shows promise for the zero-shot identification of certain sociopolitical events by achieving an F1-score of 0.52 on one wholly out-of-sample event class.
Anthology ID:
2021.case-1.25
Original:
2021.case-1.25v1
Version 2:
2021.case-1.25v2
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:
203–207
Language:
URL:
https://aclanthology.org/2021.case-1.25
DOI:
10.18653/v1/2021.case-1.25
Bibkey:
Cite (ACL):
Benjamin J. Radford. 2021. CASE 2021 Task 2: Zero-Shot Classification of Fine-Grained Sociopolitical Events with Transformer Models. In Proceedings of the 4th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE 2021), pages 203–207, Online. Association for Computational Linguistics.
Cite (Informal):
CASE 2021 Task 2: Zero-Shot Classification of Fine-Grained Sociopolitical Events with Transformer Models (Radford, CASE 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.case-1.25.pdf