Mаchine Translation Based on WordNet and Dependency Relations

Luchezar Jackov


Abstract
The proposed machine translation (MT) approach uses WordNet (Fellbaum, 1998) as a base for concepts. It identifies the concepts and dependency relations using context-free grammars (CFGs) enriched with features, role markers and dependency markers. Multiple interpretation hypotheses are generated and then are scored using a knowledge base for the dependency relations. The hypothesis with the best score is used for generating the translation. The approach has already been implemented in an MT system for seven languages, namely Bulgarian, English, French, Spanish, Italian, German, and Turkish, and also for Chinese on experimental level.
Anthology ID:
2014.clib-1.9
Volume:
Proceedings of the First International Conference on Computational Linguistics in Bulgaria (CLIB 2014)
Month:
September
Year:
2014
Address:
Sofia, Bulgaria
Venue:
CLIB
SIG:
Publisher:
Department of Computational Linguistics, Institute for Bulgarian Language, Bulgarian Academy of Sciences
Note:
Pages:
64–72
Language:
URL:
https://aclanthology.org/2014.clib-1.9
DOI:
Bibkey:
Cite (ACL):
Luchezar Jackov. 2014. Mаchine Translation Based on WordNet and Dependency Relations. In Proceedings of the First International Conference on Computational Linguistics in Bulgaria (CLIB 2014), pages 64–72, Sofia, Bulgaria. Department of Computational Linguistics, Institute for Bulgarian Language, Bulgarian Academy of Sciences.
Cite (Informal):
Mаchine Translation Based on WordNet and Dependency Relations (Jackov, CLIB 2014)
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PDF:
https://aclanthology.org/2014.clib-1.9.pdf