Some have argued that word orders which are more difficult to process
should be rarer cross-linguistically. Our current study fails to replicate
the results of Maurits, Navarro, and Perfors (2010), who used an
entropy-based Uniform Information Density (UID) measure to moderately
predict the Greenbergian typology of transitive word orders. We
additionally report an inability of three measures of processing difficulty
– entropy-based UID, surprisal-based UID, and mutual information – to
correctly predict the correct typological distribution, using transitive
constructions from 20 languages in the Universal Dependencies project
(version 2.5). However, our conclusions are limited by data sparsity.