Lessons from Computational Modelling of Reference Production in Mandarin and English

Guanyi Chen, Kees van Deemter


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
Volume:
Proceedings of the 13th International Conference on Natural Language Generation
Month:
December
Year:
2020
Address:
Dublin, Ireland
Venue:
INLG
SIG:
SIGGEN
Publisher:
Association for Computational Linguistics
Note:
Pages:
263–272
Language:
URL:
https://www.aclweb.org/anthology/2020.inlg-1.33
DOI:
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PDF:
http://aclanthology.lst.uni-saarland.de/2020.inlg-1.33.pdf
Supplementary attachment:
 2020.inlg-1.33.Supplementary_Attachment.pdf