Translating Legal Sentence by Segmentation and Rule Selection
نویسندگان
چکیده
A legal text usually long and complicated, it has some characteristic that make it different from other dailyuse texts.Then, translating a legal text is generally considered to be difficult. This paper introduces an approach to split a legal sentence based on its logical structure and presents selecting appropriate translation rules to improve phrase reordering of legal translation. We use a method which divides a English legal sentence based on its logical structure to segment the legal sentence. New features with rich linguistic and contextual information of split sentences are proposed to rule selection. We apply maximum entropy to combine rich linguistic and contextual information and integrate the features of split sentences into the legal translation, tree-based SMT system. We obtain improvements in performance for legal translation from English to Japanese over Moses and Moses-chart systems.
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