Predicting Japanese Word Order in Double Object Constructions
Masayuki Asahara, Satoshi Nambu, Shin–ichiro Sano · 2018
This paper presents a statistical model to predict Japanese word order in the double object constructions.We employed a Bayesian linear mixed model with manually annotated predicate-argument structure data.The findings from the refined corpus analysis confirmed the effects of information status of an NP as 'givennew ordering' in addition to the effects of 'long-before-short' as a tendency of the general Japanese word order.