Local phrase reordering model for complicated Chinese NPs in patent Chinese-English machine translation

Abstract

We focused on when and how to reorder the complicated Chinese NPs with two, three, four or five semantic-units and the semantic units were smallest chunks for reordering in Chinese-English Machine Translation. By analyzing clear parallels and striking distinctions between complicated Chinese NPs and their English, we built 17 formalized rules to identify the boundaries of semantic units with the Boundary-Words deduced from semantic features to recognized what to reorder and developed a strategy on how to reorder the internal ordering of complicated Chinese NPs when translated into English. At last, we used a rule-based MT system to test our work, and the experimental results showed that our strategy and rule-based method were very efficient.