@inproceedings{wang-etal-2020-semeval,
title = "{S}em{E}val-2020 Task 4: Commonsense Validation and Explanation",
author = "Wang, Cunxiang and
Liang, Shuailong and
Jin, Yili and
Wang, Yilong and
Zhu, Xiaodan and
Zhang, Yue",
editor = "Herbelot, Aurelie and
Zhu, Xiaodan and
Palmer, Alexis and
Schneider, Nathan and
May, Jonathan and
Shutova, Ekaterina",
booktitle = "Proceedings of the Fourteenth Workshop on Semantic Evaluation",
month = dec,
year = "2020",
address = "Barcelona (online)",
publisher = "International Committee for Computational Linguistics",
url = "https://aclanthology.org/2020.semeval-1.39/",
doi = "10.18653/v1/2020.semeval-1.39",
pages = "307--321",
abstract = "In this paper, we present SemEval-2020 Task 4, Commonsense Validation and Explanation (ComVE), which includes three subtasks, aiming to evaluate whether a system can distinguish a natural language statement that makes sense to humans from one that does not, and provide the reasons. Specifically, in our first subtask, the participating systems are required to choose from two natural language statements of similar wording the one that makes sense and the one does not. The second subtask additionally asks a system to select the key reason from three options why a given statement does not make sense. In the third subtask, a participating system needs to generate the reason automatically. 39 teams submitted their valid systems to at least one subtask. For Subtask A and Subtask B, top-performing teams have achieved results closed to human performance. However, for Subtask C, there is still a considerable gap between system and human performance. The dataset used in our task can be found at \url{https://github.com/wangcunxiang/SemEval2020-Task4-Commonsense-Validation-and-Explanation}."
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<abstract>In this paper, we present SemEval-2020 Task 4, Commonsense Validation and Explanation (ComVE), which includes three subtasks, aiming to evaluate whether a system can distinguish a natural language statement that makes sense to humans from one that does not, and provide the reasons. Specifically, in our first subtask, the participating systems are required to choose from two natural language statements of similar wording the one that makes sense and the one does not. The second subtask additionally asks a system to select the key reason from three options why a given statement does not make sense. In the third subtask, a participating system needs to generate the reason automatically. 39 teams submitted their valid systems to at least one subtask. For Subtask A and Subtask B, top-performing teams have achieved results closed to human performance. However, for Subtask C, there is still a considerable gap between system and human performance. The dataset used in our task can be found at https://github.com/wangcunxiang/SemEval2020-Task4-Commonsense-Validation-and-Explanation.</abstract>
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%0 Conference Proceedings
%T SemEval-2020 Task 4: Commonsense Validation and Explanation
%A Wang, Cunxiang
%A Liang, Shuailong
%A Jin, Yili
%A Wang, Yilong
%A Zhu, Xiaodan
%A Zhang, Yue
%Y Herbelot, Aurelie
%Y Zhu, Xiaodan
%Y Palmer, Alexis
%Y Schneider, Nathan
%Y May, Jonathan
%Y Shutova, Ekaterina
%S Proceedings of the Fourteenth Workshop on Semantic Evaluation
%D 2020
%8 December
%I International Committee for Computational Linguistics
%C Barcelona (online)
%F wang-etal-2020-semeval
%X In this paper, we present SemEval-2020 Task 4, Commonsense Validation and Explanation (ComVE), which includes three subtasks, aiming to evaluate whether a system can distinguish a natural language statement that makes sense to humans from one that does not, and provide the reasons. Specifically, in our first subtask, the participating systems are required to choose from two natural language statements of similar wording the one that makes sense and the one does not. The second subtask additionally asks a system to select the key reason from three options why a given statement does not make sense. In the third subtask, a participating system needs to generate the reason automatically. 39 teams submitted their valid systems to at least one subtask. For Subtask A and Subtask B, top-performing teams have achieved results closed to human performance. However, for Subtask C, there is still a considerable gap between system and human performance. The dataset used in our task can be found at https://github.com/wangcunxiang/SemEval2020-Task4-Commonsense-Validation-and-Explanation.
%R 10.18653/v1/2020.semeval-1.39
%U https://aclanthology.org/2020.semeval-1.39/
%U https://doi.org/10.18653/v1/2020.semeval-1.39
%P 307-321
Markdown (Informal)
[SemEval-2020 Task 4: Commonsense Validation and Explanation](https://aclanthology.org/2020.semeval-1.39/) (Wang et al., SemEval 2020)
ACL
- Cunxiang Wang, Shuailong Liang, Yili Jin, Yilong Wang, Xiaodan Zhu, and Yue Zhang. 2020. SemEval-2020 Task 4: Commonsense Validation and Explanation. In Proceedings of the Fourteenth Workshop on Semantic Evaluation, pages 307–321, Barcelona (online). International Committee for Computational Linguistics.