数据集:
tasksource/sen-making
https://github.com/wangcunxiang/Sen-Making-and-Explanation
@inproceedings{wang-etal-2019-make, title = "Does it Make Sense? And Why? A Pilot Study for Sense Making and Explanation", author = "Wang, Cunxiang and Liang, Shuailong and Zhang, Yue and Li, Xiaonan and Gao, Tian", booktitle = "Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics", month = jul, year = "2019", address = "Florence, Italy", publisher = "Association for Computational Linguistics", url = "https://www.aclweb.org/anthology/P19-1393", pages = "4020--4026", abstract = "Introducing common sense to natural language understanding systems has received increasing research attention. It remains a fundamental question on how to evaluate whether a system has the sense-making capability. Existing benchmarks measure common sense knowledge indirectly or without reasoning. In this paper, we release a benchmark to directly test whether a system can differentiate natural language statements that make sense from those that do not make sense. In addition, a system is asked to identify the most crucial reason why a statement does not make sense. We evaluate models trained over large-scale language modeling tasks as well as human performance, showing that there are different challenges for system sense-making.", }