  Across languages, multiple consecutive adjectives modifying a noun (e.g. "the
big red dog") follow certain unmarked ordering rules. While explanatory
accounts have been put forward, much of the work done in this area has relied
primarily on the intuitive judgment of native speakers, rather than on corpus
data. We present the first purely corpus-driven model of multi-lingual
adjective ordering in the form of a latent-variable model that can accurately
order adjectives across 24 different languages, even when the training and
testing languages are different. We utilize this novel statistical model to
provide strong converging evidence for the existence of universal,
cross-linguistic, hierarchical adjective ordering tendencies.
