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
- 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)
- PDF:
- https://preview.aclanthology.org/emnlp-22-attachments/W18-6519.pdf