Abstract
Referring expression generation (REG) algorithms offer computational models of the production of referring expressions. In earlier work, a corpus of referring expressions (REs) in Mandarin was introduced. In the present paper, we annotate this corpus, evaluate classic REG algorithms on it, and compare the results with earlier results on the evaluation of REG for English referring expressions. Next, we offer an in-depth analysis of the corpus, focusing on issues that arise from the grammar of Mandarin. We discuss shortcomings of previous REG evaluations that came to light during our investigation and we highlight some surprising results. Perhaps most strikingly, we found a much higher proportion of under-specified expressions than previous studies had suggested, not just in Mandarin but in English as well.- Anthology ID:
- 2020.inlg-1.33
- Original:
- 2020.inlg-1.33v1
- Version 2:
- 2020.inlg-1.33v2
- Volume:
- Proceedings of the 13th International Conference on Natural Language Generation
- Month:
- December
- Year:
- 2020
- Address:
- Dublin, Ireland
- Editors:
- Brian Davis, Yvette Graham, John Kelleher, Yaji Sripada
- Venue:
- INLG
- SIG:
- SIGGEN
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 263–272
- Language:
- URL:
- https://aclanthology.org/2020.inlg-1.33
- DOI:
- 10.18653/v1/2020.inlg-1.33
- Cite (ACL):
- Guanyi Chen and Kees van Deemter. 2020. Lessons from Computational Modelling of Reference Production in Mandarin and English. In Proceedings of the 13th International Conference on Natural Language Generation, pages 263–272, Dublin, Ireland. Association for Computational Linguistics.
- Cite (Informal):
- Lessons from Computational Modelling of Reference Production in Mandarin and English (Chen & van Deemter, INLG 2020)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-3/2020.inlg-1.33.pdf