Noun classes (genders) have long played an important role in the understanding of language structure and human categorization. The current study presents and analyzes the division of nouns into classes in Tsez (Dido), an endangered Nakh-Dagestanian language of the Northeast Caucasus. Computational modeling of the Tsez system shows that noun classification in Tsez is highly predictable, with a simple semantic core and a set of highly salient formal features, that can be ranked with respect to one another. Such a system would be easily accessible to children acquiring the language, and the proposed analysis does not require additional semantic or categorical assumptions. The study serves as a proof of principle for the computational approach to the analysis of noun classification.
This chapter reanalyses noun classification in the Australian language Dyirbal. While earlier analyses have proposed intricate class assignment principles rooted in conceptual features, we argue that Dyirbal noun classification is sensitive to salient phonological cues and a small core of cross‐linguistically common semantic cues in keeping with other familiar noun classification systems.