Find a reasonable ending for stories: Does logic relation help the story cloze test?

Shang，Mingyue1; Fu，Zhenxin1; Yin，Hongzhi2; Tang，Bo4; Zhao，Dongyan1,3; Yan，Rui1,3

2019

33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Innovative Applications of Artificial Intelligence Conference, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019

10031-10032

Natural language understanding is a challenging problem that covers a wide range of tasks. While previous methods generally train each task separately, we consider combining the cross-task features to enhance the task performance. In this paper, we incorporate the logic information with the help of the Natural Language Inference (NLI) task to the Story Cloze Test (SCT). Previous work on SCT considered various semantic information, such as sentiment and topic, but lack the logic information between sentences which is an essential element of stories. Thus we propose to extract the logic information during the course of the story to improve the understanding of the whole story. The logic information is modeled with the help of the NLI task. Experimental results prove the strength of the logic information.

其他

英语

EI

20203509101318

Artificial intelligence ; Computer circuits

Computer Circuits:721.3 ; Artificial Intelligence:723.4

2-s2.0-85090800191

Scopus

1.Institute of Computer Science and Technology,Peking University,China
2.University of Queensland,Australia
3.Center for Data Science,Peking University,China
4.Southern University of Science and Technology,China

Shang，Mingyue,Fu，Zhenxin,Yin，Hongzhi,et al. Find a reasonable ending for stories: Does logic relation help the story cloze test?[C],2019:10031-10032.