A Multi-Attention based Neural Network with External Knowledge for Story Ending Predicting Task
Qian Li, Ziwei Li, Jin-Mao Wei, Yanhui Gu, Adam Jatowt, Zhenglu Yang
Abstract
Enabling a mechanism to understand a temporal story and predict its ending is an interesting issue that has attracted considerable attention, as in case of the ROC Story Cloze Task (SCT). In this paper, we develop a multi-attention-based neural network (MANN) with well-designed optimizations, like Highway Network, and concatenated features with embedding representations into the hierarchical neural network model. Considering the particulars of the specific task, we thoughtfully extend MANN with external knowledge resources, exceeding state-of-the-art results obviously. Furthermore, we develop a thorough understanding of our model through a careful hand analysis on a subset of the stories. We identify what traits of MANN contribute to its outperformance and how external knowledge is obtained in such an ending prediction task.- Anthology ID:
- C18-1149
- Volume:
- Proceedings of the 27th International Conference on Computational Linguistics
- Month:
- August
- Year:
- 2018
- Address:
- Santa Fe, New Mexico, USA
- Editors:
- Emily M. Bender, Leon Derczynski, Pierre Isabelle
- Venue:
- COLING
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 1754–1762
- Language:
- URL:
- https://aclanthology.org/C18-1149
- DOI:
- Cite (ACL):
- Qian Li, Ziwei Li, Jin-Mao Wei, Yanhui Gu, Adam Jatowt, and Zhenglu Yang. 2018. A Multi-Attention based Neural Network with External Knowledge for Story Ending Predicting Task. In Proceedings of the 27th International Conference on Computational Linguistics, pages 1754–1762, Santa Fe, New Mexico, USA. Association for Computational Linguistics.
- Cite (Informal):
- A Multi-Attention based Neural Network with External Knowledge for Story Ending Predicting Task (Li et al., COLING 2018)
- PDF:
- https://preview.aclanthology.org/naacl24-info/C18-1149.pdf
- Data
- StoryCloze