Predicting Japanese Word Order in Double Object Constructions
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.
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