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CSG-Tag: Constraint based synchronous grammar tree annotation system
Wong F.; Oliveira F.; Chao S.; Sun F.
2011-11-07
Conference Name2011 International Conference on Machine Learning and Cybernetics
Source PublicationProceedings - International Conference on Machine Learning and Cybernetics
Volume4
Pages1472-1478
Conference Date10-13 July 2011
Conference PlaceGuilin, China
Abstract

The construction of grammars and the acquisition of syntactic structures from corpora are always considered as a time consuming task. Moreover, according to the purpose of the application, different standards have to be defined. In Machine Translation (MT), the situation is even more complicated since it covers two languages. In this paper, CSG-Tag, a Constraint based Synchronous Grammar (CSG) Tree Annotation System is proposed. This system provides a semi-automatic annotation process in the creation of syntactic structure of the source sentence linked with the corresponding target sentential patterns. All learned information are stored in Extensible Markup Language (XML) format and can be converted into grammar rules in application to MT. Moreover, the system has a function to import monolingual skeletal bracketing syntactic tree and Translation Corresponding Tree (TCT) structures in the creation of CSG rules. © 2011 IEEE.

KeywordConstraint Synchronous Grammar Machine Translation Translation Corresponding Tree Tree Annotation System
DOI10.1109/ICMLC.2011.6017024
URLView the original
Language英語English
Scopus ID2-s2.0-80155125452
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Citation statistics
Document TypeConference paper
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
AffiliationUniversidade de Macau
First Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Wong F.,Oliveira F.,Chao S.,et al. CSG-Tag: Constraint based synchronous grammar tree annotation system[C], 2011, 1472-1478.
APA Wong F.., Oliveira F.., Chao S.., & Sun F. (2011). CSG-Tag: Constraint based synchronous grammar tree annotation system. Proceedings - International Conference on Machine Learning and Cybernetics, 4, 1472-1478.
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