HUMAN & MACHINE INTELLIGENCE

NLP

Measuring the Similarity of Grammatical Gender Systems by Comparing Partitions

November 16, 2020

Abstract

A grammatical gender system divides a lexicon into a small number of relatively fixed grammatical categories. How similar are these gender systems across languages? To quantify the similarity, we define gender systems extensionally, thereby reducing the problem of comparisons between languages’ gender systems to cluster evaluation. We borrow a rich inventory of statistical tools for cluster evaluation from the field of community detection (Driver and Kroeber, 1932; Cattell, 1945), that enable us to craft novel information-theoretic metrics for measuring similarity between gender systems. We first validate our metrics, then use them to measure gender system similarity in 20 languages. Finally, we ask whether our gender system similarities alone are sufficient to reconstruct historical relationships between languages. Towards this end, we make phylogenetic predictions on the popular, but thorny, problem from historical linguistics of inducing a phylogenetic tree over extant Indo-European languages. Languages on the same branch of our phylogenetic tree are notably similar, whereas languages from separate branches are no more similar than chance.

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AUTHORS

Written by

Arya D. McCarthy

Adina Williams

Shijia Liu

David Yarowsky

Ryan Cotterell

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