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
Venue:
IJCNLP
SIG:
Publisher:
Asian Federation of Natural Language Processing
Note:
Pages:
37–42
Language:
URL:
https://aclanthology.org/I17-2007
DOI:
Bibkey:
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)
Copy Citation:
PDF:
https://aclanthology.org/I17-2007.pdf
Code
 daiquocnguyen/EventPrediction