Work

Does it Make Sense? And Why? A Pilot Study for Sense Making and Explanation

Year: 2019

Type: conference-paper

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 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.

Source: Annual Meeting of the Association for Computational Linguistics (ACL)

DOI: 10.18653/v1/p19-1393

Authors: Cunxiang Wang, Shuailong Liang, Yue Zhang, Xiaonan Li, Tian Gao

Institutions: Westlake University, Zhejiang University, Singapore University of Technology and Design, Xidian University

Language: English

Topic: Topic Modeling

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Funder: National Natural Science Foundation of China

Award: 句法语义分析与开放域信息抽取融合技术研究