Hongru Wang
2020
CUHK at SemEval-2020 Task 4: CommonSense Explanation, Reasoning and Prediction with Multi-task Learning
Hongru Wang
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Xiangru Tang
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Sunny Lai
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Kwong Sak Leung
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Jia Zhu
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Gabriel Pui Cheong Fung
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Kam-Fai Wong
Proceedings of the Fourteenth Workshop on Semantic Evaluation
This paper describes our system submitted to task 4 of SemEval 2020: Commonsense Validation and Explanation (ComVE) which consists of three sub-tasks. The task is to directly validate the given sentence whether or not to make sense and require the model to explain it. Based on BERT architecture with the multi-task setting, we propose an effective and interpretable “Explain, Reason and Predict” (ERP) system to solve the three sub-tasks about commonsense: (a) Validation, (b) Reasoning, and (c) Explanation. Inspired by cognitive studies of common sense, our system first generates a reason or understanding of the sentences and then choose which one statement makes sense, which is achieved by multi-task learning. During the post-evaluation, our system has reached 92.9% accuracy in subtask A (rank 11), 89.7% accuracy in subtask B (rank 9), and BLEU score of 12.9 in subtask C (rank 8).
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Co-authors
- Xiangru Tang 1
- Sunny Lai 1
- Kwong Sak Leung 1
- Jia Zhu 1
- Gabriel Pui Cheong Fung 1
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