Does it Make Sense? And Why? A Pilot Study for Sense Making and Explanation
Cunxiang Wang, Shuailong Liang, Yue Zhang, Xiaonan Li, Tian Gao · 2019
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 a sense making capability.Existing benchmarks measures commonsense knowledge indirectly and without explanation.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.