Investigating Cross-Linguistic Adjective Ordering Tendencies with a Latent-Variable Model

EMNLP 2020  ·  Jun Yen Leung, Guy Emerson, Ryan Cotterell ·

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.

PDF Abstract EMNLP 2020 PDF EMNLP 2020 Abstract
No code implementations yet. Submit your code now

Tasks


Results from the Paper


  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods


No methods listed for this paper. Add relevant methods here