Abstract
We describe the system submitted by the SWAGex team to the SemEval-2020 Commonsense Validation and Explanation Task. We use multiple methods on the pre-trained language model BERT (Devlin et al., 2018) for tasks that require the system to recognize sentences against commonsense and justify the reasoning behind this decision. Our best performing model is BERT trained on SWAG and fine-tuned for the task. We investigate the ability to transfer commonsense knowledge from SWAG to SemEval-2020 by training a model for the Explanation task with Next Event Prediction data- Anthology ID:
- 2020.semeval-1.51
- Volume:
- Proceedings of the Fourteenth Workshop on Semantic Evaluation
- Month:
- December
- Year:
- 2020
- Address:
- Barcelona (online)
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- International Committee for Computational Linguistics
- Note:
- Pages:
- 422–429
- Language:
- URL:
- https://aclanthology.org/2020.semeval-1.51
- DOI:
- 10.18653/v1/2020.semeval-1.51
- Cite (ACL):
- Wiem Ben Rim and Naoaki Okazaki. 2020. SWAGex at SemEval-2020 Task 4: Commonsense Explanation as Next Event Prediction. In Proceedings of the Fourteenth Workshop on Semantic Evaluation, pages 422–429, Barcelona (online). International Committee for Computational Linguistics.
- Cite (Informal):
- SWAGex at SemEval-2020 Task 4: Commonsense Explanation as Next Event Prediction (Ben Rim & Okazaki, SemEval 2020)
- PDF:
- https://preview.aclanthology.org/nodalida-main-page/2020.semeval-1.51.pdf
- Data
- SWAG