Abstract
I briefly describe some of the commercial work which Arria NLG is doing in referring expression algorithms, and highlight differences between what is commercially important (at least to Arria) and the NLG research literature. Arria's focus is on high-quality algorithms for types of reference which are important in its systems. These algorithms need to be parametrisable for different genres and domains, usable in hybrid systems which include some canned text, and support variation.
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CITATION STYLE
Reiter, E. (2017). A commercial perspective on reference. In INLG 2017 - 10th International Natural Language Generation Conference, Proceedings of the Conference (pp. 134–138). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/w17-3519
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