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
- Venue:
- CASE
- 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
- 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)
- PDF:
- https://preview.aclanthology.org/remove-xml-comments/2021.case-1.25.pdf