Let’s do it “again”: A First Computational Approach to Detecting Adverbial Presupposition Triggers
Andre Cianflone, Yulan Feng, Jad Kabbara, Jackie Chi Kit Cheung
Abstract
We introduce the novel task of predicting adverbial presupposition triggers, which is useful for natural language generation tasks such as summarization and dialogue systems. We introduce two new corpora, derived from the Penn Treebank and the Annotated English Gigaword dataset and investigate the use of a novel attention mechanism tailored to this task. Our attention mechanism augments a baseline recurrent neural network without the need for additional trainable parameters, minimizing the added computational cost of our mechanism. We demonstrate that this model statistically outperforms our baselines.- Anthology ID:
- P18-1256
- Volume:
- Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
- Month:
- July
- Year:
- 2018
- Address:
- Melbourne, Australia
- Editors:
- Iryna Gurevych, Yusuke Miyao
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 2747–2755
- Language:
- URL:
- https://aclanthology.org/P18-1256
- DOI:
- 10.18653/v1/P18-1256
- Cite (ACL):
- Andre Cianflone, Yulan Feng, Jad Kabbara, and Jackie Chi Kit Cheung. 2018. Let’s do it “again”: A First Computational Approach to Detecting Adverbial Presupposition Triggers. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 2747–2755, Melbourne, Australia. Association for Computational Linguistics.
- Cite (Informal):
- Let’s do it “again”: A First Computational Approach to Detecting Adverbial Presupposition Triggers (Cianflone et al., ACL 2018)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/P18-1256.pdf
- Data
- Penn Treebank