ISCAS at SemEval-2020 Task 5: Pre-trained Transformers for Counterfactual Statement Modeling

Yaojie Lu, Annan Li, Hongyu Lin, Xianpei Han, Le Sun


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
SIGs:
SIGLEX | SIGSEM
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
Bibkey:
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)
Copy Citation:
PDF:
https://aclanthology.org/2020.semeval-1.85.pdf
Code
 casnlu/ISCAS-SemEval2020Task5