Sequence to Sequence Learning for Event Prediction
Dai Quoc Nguyen, Dat Quoc Nguyen, Cuong Xuan Chu, Stefan Thater, Manfred Pinkal
Abstract
This paper presents an approach to the task of predicting an event description from a preceding sentence in a text. Our approach explores sequence-to-sequence learning using a bidirectional multi-layer recurrent neural network. Our approach substantially outperforms previous work in terms of the BLEU score on two datasets derived from WikiHow and DeScript respectively. Since the BLEU score is not easy to interpret as a measure of event prediction, we complement our study with a second evaluation that exploits the rich linguistic annotation of gold paraphrase sets of events.- Anthology ID:
- I17-2007
- Volume:
- Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 2: Short Papers)
- Month:
- November
- Year:
- 2017
- Address:
- Taipei, Taiwan
- Editors:
- Greg Kondrak, Taro Watanabe
- Venue:
- IJCNLP
- SIG:
- Publisher:
- Asian Federation of Natural Language Processing
- Note:
- Pages:
- 37–42
- Language:
- URL:
- https://aclanthology.org/I17-2007
- DOI:
- Cite (ACL):
- Dai Quoc Nguyen, Dat Quoc Nguyen, Cuong Xuan Chu, Stefan Thater, and Manfred Pinkal. 2017. Sequence to Sequence Learning for Event Prediction. In Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 2: Short Papers), pages 37–42, Taipei, Taiwan. Asian Federation of Natural Language Processing.
- Cite (Informal):
- Sequence to Sequence Learning for Event Prediction (Nguyen et al., IJCNLP 2017)
- PDF:
- https://preview.aclanthology.org/naacl24-info/I17-2007.pdf
- Code
- daiquocnguyen/EventPrediction