Abstract
ISCAS participated in two subtasks of SemEval 2020 Task 5: detecting counterfactual statements and detecting antecedent and consequence. This paper describes our system which is based on pretrained transformers. For the first subtask, we train several transformer-based classifiers for detecting counterfactual statements. For the second subtask, we formulate antecedent and consequence extraction as a query-based question answering problem. The two subsystems both achieved third place in the evaluation. Our system is openly released at https://github.com/casnlu/ISCASSemEval2020Task5.- Anthology ID:
- 2020.semeval-1.85
- 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:
- 658–663
- Language:
- URL:
- https://aclanthology.org/2020.semeval-1.85
- DOI:
- 10.18653/v1/2020.semeval-1.85
- Cite (ACL):
- Yaojie Lu, Annan Li, Hongyu Lin, Xianpei Han, and Le Sun. 2020. ISCAS at SemEval-2020 Task 5: Pre-trained Transformers for Counterfactual Statement Modeling. In Proceedings of the Fourteenth Workshop on Semantic Evaluation, pages 658–663, Barcelona (online). International Committee for Computational Linguistics.
- Cite (Informal):
- ISCAS at SemEval-2020 Task 5: Pre-trained Transformers for Counterfactual Statement Modeling (Lu et al., SemEval 2020)
- PDF:
- https://preview.aclanthology.org/remove-xml-comments/2020.semeval-1.85.pdf
- Code
- casnlu/ISCAS-SemEval2020Task5