Incorporating Structured Commonsense Knowledge in Story Completion

Authors

  • Jiaao Chen Zhejiang University
  • Jianshu Chen Tencent
  • Zhou Yu University of California, Davis

DOI:

https://doi.org/10.1609/aaai.v33i01.33016244

Abstract

The ability to select an appropriate story ending is the first step towards perfect narrative comprehension. Story ending prediction requires not only the explicit clues within the context, but also the implicit knowledge (such as commonsense) to construct a reasonable and consistent story. However, most previous approaches do not explicitly use background commonsense knowledge. We present a neural story ending selection model that integrates three types of information: narrative sequence, sentiment evolution and commonsense knowledge. Experiments show that our model outperforms state-ofthe-art approaches on a public dataset, ROCStory Cloze Task (Mostafazadeh et al. 2017), and the performance gain from adding the additional commonsense knowledge is significant.

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Published

2019-07-17

How to Cite

Chen, J., Chen, J., & Yu, Z. (2019). Incorporating Structured Commonsense Knowledge in Story Completion. Proceedings of the AAAI Conference on Artificial Intelligence, 33(01), 6244-6251. https://doi.org/10.1609/aaai.v33i01.33016244

Issue

Section

AAAI Technical Track: Natural Language Processing