Specificity measures and reference

Albert Gatt, Nicolás Marín, Gustavo Rivas-Gervilla, Daniel Sánchez

Abstract
In this paper we study empirically the validity of measures of referential success for referring expressions involving gradual properties. More specifically, we study the ability of several measures of referential success to predict the success of a user in choosing the right object, given a referring expression. Experimental results indicate that certain fuzzy measures of success are able to predict human accuracy in reference resolution. Such measures are therefore suitable for the estimation of the success or otherwise of a referring expression produced by a generation algorithm, especially in case the properties in a domain cannot be assumed to have crisp denotations.
Anthology ID:
W18-6562
Volume:
Proceedings of the 11th International Conference on Natural Language Generation
Month:
November
Year:
2018
Address:
Tilburg University, The Netherlands
Editors:
Emiel Krahmer, Albert Gatt, Martijn Goudbeek
Venue:
INLG
SIG:
SIGGEN
Publisher:
Association for Computational Linguistics
Note:
Pages:
492–502
Language:
URL:
https://aclanthology.org/W18-6562
DOI:
10.18653/v1/W18-6562
Bibkey:
Cite (ACL):
Albert Gatt, Nicolás Marín, Gustavo Rivas-Gervilla, and Daniel Sánchez. 2018. Specificity measures and reference. In Proceedings of the 11th International Conference on Natural Language Generation, pages 492–502, Tilburg University, The Netherlands. Association for Computational Linguistics.
Cite (Informal):
Specificity measures and reference (Gatt et al., INLG 2018)
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PDF:
https://preview.aclanthology.org/nschneid-patch-5/W18-6562.pdf
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