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Improving Parsing of ‘BA’ Sentences for Machine Translation
Author(s) -
Yin Dapeng,
Shao Min,
Ren Fuji,
Kuroiwa Shingo
Publication year - 2008
Publication title -
ieej transactions on electrical and electronic engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.254
H-Index - 30
eISSN - 1931-4981
pISSN - 1931-4973
DOI - 10.1002/tee.20241
Subject(s) - computer science , natural language processing , sentence , artificial intelligence , parsing , machine translation , transfer based machine translation , example based machine translation , grammar , object (grammar) , rule based machine translation , translation (biology) , linguistics , philosophy , biochemistry , chemistry , messenger rna , gene
The research on Chinese‐Japanese machine translation has been lasting for many years, and now this research field is increasingly thoroughly refined. In practical machine translation system, the processing of a simple and short Chinese sentence has somewhat good results. However, the translation of complex long Chinese sentence still has difficulties. For example, these systems are still unable to solve the translation problem of complex ‘BA’ sentences. In this article a new method of parsing of ‘BA’ sentence for machine translation based on valency theory is proposed. A ‘BA’ sentence is one that has a prepositional word ‘BA’. The structural character of a ‘BA’ sentence is that the original verb is behind the object word. The object word after the ‘BA’ preposition is used as an adverbial modifier of an active word. First, a large number of grammar items from Chinese grammar books are collected, and some elementary judgment rules are set by classifying and including the collected grammar items. Then, these judgment rules are put into use in actual Chinese language and are modified by checking their results instantly. Rules are checked and modified by using the statistical information from an actual corpus. Then, a five‐segment model used for ‘BA’ sentence translation is brought forward after the above mentioned analysis. Finally, we applied this proposed model into our developed machine translation system and evaluated the experimental results. It achieved a 91.3% rate of accuracy and the satisfying result verified effectiveness of our five‐segment model for ‘BA’ sentence translation. Copyright © 2007 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.