Modelling Pro-drop with the Rational Speech Acts Model

Guanyi Chen, Kees van Deemter, Chenghua Lin


Abstract
We extend the classic Referring Expressions Generation task by considering zero pronouns in “pro-drop” languages such as Chinese, modelling their use by means of the Bayesian Rational Speech Acts model (Frank and Goodman, 2012). By assuming that highly salient referents are most likely to be referred to by zero pronouns (i.e., pro-drop is more likely for salient referents than the less salient ones), the model offers an attractive explanation of a phenomenon not previously addressed probabilistically.
Anthology ID:
W18-6519
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:
159–164
Language:
URL:
https://aclanthology.org/W18-6519
DOI:
10.18653/v1/W18-6519
Bibkey:
Cite (ACL):
Guanyi Chen, Kees van Deemter, and Chenghua Lin. 2018. Modelling Pro-drop with the Rational Speech Acts Model. In Proceedings of the 11th International Conference on Natural Language Generation, pages 159–164, Tilburg University, The Netherlands. Association for Computational Linguistics.
Cite (Informal):
Modelling Pro-drop with the Rational Speech Acts Model (Chen et al., INLG 2018)
Copy Citation:
PDF:
https://aclanthology.org/W18-6519.pdf