Modeling Event Background for If-Then Commonsense Reasoning Using Context-aware Variational Autoencoder

Li Du, Xiao Ding, Ting Liu, Zhongyang Li


Abstract
Understanding event and event-centered commonsense reasoning are crucial for natural language processing (NLP). Given an observed event, it is trivial for human to infer its intents and effects, while this type of If-Then reasoning still remains challenging for NLP systems. To facilitate this, a If-Then commonsense reasoning dataset Atomic is proposed, together with an RNN-based Seq2Seq model to conduct such reasoning. However, two fundamental problems still need to be addressed: first, the intents of an event may be multiple, while the generations of RNN-based Seq2Seq models are always semantically close; second, external knowledge of the event background may be necessary for understanding events and conducting the If-Then reasoning. To address these issues, we propose a novel context-aware variational autoencoder effectively learning event background information to guide the If-Then reasoning. Experimental results show that our approach improves the accuracy and diversity of inferences compared with state-of-the-art baseline methods.
Anthology ID:
D19-1270
Volume:
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)
Month:
November
Year:
2019
Address:
Hong Kong, China
Venues:
EMNLP | IJCNLP
SIG:
SIGDAT
Publisher:
Association for Computational Linguistics
Note:
Pages:
2682–2691
Language:
URL:
https://aclanthology.org/D19-1270
DOI:
10.18653/v1/D19-1270
Bibkey:
Cite (ACL):
Li Du, Xiao Ding, Ting Liu, and Zhongyang Li. 2019. Modeling Event Background for If-Then Commonsense Reasoning Using Context-aware Variational Autoencoder. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), pages 2682–2691, Hong Kong, China. Association for Computational Linguistics.
Cite (Informal):
Modeling Event Background for If-Then Commonsense Reasoning Using Context-aware Variational Autoencoder (Du et al., EMNLP-IJCNLP 2019)
Copy Citation:
PDF:
https://aclanthology.org/D19-1270.pdf
Data
Event2MindROCStoriesVISTWritingPrompts