Verifying the Menzerath-Altmann law in the verbal domain in 180 languages

Abstract

We present a large-scale evaluation of the Menzerath-Altmann law (MAL) in the verbal domain across 180 languages, using the Universal Dependencies (UD) treebank collection (v2.17). MAL predicts that as the number of constituents of a linguistic unit increases, their average size decreases. We propose a robust metric to estimate the MAL effect across corpora of widely varying sizes and define threshold-based categories to classify languages along a MAL preference cline. Crucially, we analyse the preverbal and postverbal domains separately, in addition to the standard bilateral MAL, and control for potential sampling bias by comparing results across language families (Indo-European vs. non-Indo-European) and syntactic types (VO, OV and no dominant order). Our results confirm MAL as a typologically widespread preference but not an absolute universal: several languages display a trivial or even opposite (anti-MAL) tendency. Furthermore, we uncover a significant asymmetry between the two sides of the verb: the MAL effect is stronger in the postverbal domain, while anti-MAL is stronger in the preverbal domain. VO languages tend to show a stronger MAL preference postverbally, whereas OV languages do so preverbally. These findings challenge the widespread assumption that length-based ordering constraints apply symmetrically on both sides of the verb and contribute new cross-linguistic evidence to the debate on the interaction between dependency length minimization and constituent size.

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