Jani Järnfors


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Using BERT for choosing classifiers in Mandarin
Jani Järnfors | Guanyi Chen | Kees van Deemter | Rint Sybesma
Proceedings of the 14th International Conference on Natural Language Generation

Choosing the most suitable classifier in a linguistic context is a well-known problem in the production of Mandarin and many other languages. The present paper proposes a solution based on BERT, compares this solution to previous neural and rule-based models, and argues that the BERT model performs particularly well on those difficult cases where the classifier adds information to the text.