2018
ACL
ACL 2018
Predicting Japanese Word Order in Double Object Constructions
Abstract
AbstractThis 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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Interdisciplinary Bridge
— Interdisciplinary and Machine Learning
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Trend Setter
— Syntax
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Keyword Pioneer
— bayesian linear mixed model
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Hot Topic Early Bird
— japanese language
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Speech & Audio