Generating Contrastive Referring Expressions

Martín Villalba, Christoph Teichmann, Alexander Koller


Abstract
The referring expressions (REs) produced by a natural language generation (NLG) system can be misunderstood by the hearer, even when they are semantically correct. In an interactive setting, the NLG system can try to recognize such misunderstandings and correct them. We present an algorithm for generating corrective REs that use contrastive focus (“no, the BLUE button”) to emphasize the information the hearer most likely misunderstood. We show empirically that these contrastive REs are preferred over REs without contrast marking.
Anthology ID:
P17-1063
Volume:
Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Month:
July
Year:
2017
Address:
Vancouver, Canada
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
678–687
Language:
URL:
https://aclanthology.org/P17-1063
DOI:
10.18653/v1/P17-1063
Bibkey:
Cite (ACL):
Martín Villalba, Christoph Teichmann, and Alexander Koller. 2017. Generating Contrastive Referring Expressions. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 678–687, Vancouver, Canada. Association for Computational Linguistics.
Cite (Informal):
Generating Contrastive Referring Expressions (Villalba et al., ACL 2017)
Copy Citation:
PDF:
https://aclanthology.org/P17-1063.pdf
Dataset:
 P17-1063.Datasets.zip
Video:
 https://vimeo.com/234957432