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Example-based Machine Translation from English to Farsi with the help of WordNet Ontology
Machine translation is a process of automatic translation from one language to another. In the present study, architecture was proposed for the system of example-based machine translation from English to Farsi with the help of WordNet ontology. This system uses a knowledge base containing a set of examples, a bilingual dictionary and WordNet. An effective factor in quality of translation is ambiguity in selecting one of the different meanings that a word can have while being translated from one language to another. In the proposed method of the present study, WorldNet is utilized in the formation phase of example set and the adaptation phase so that ambiguity in translation can be reduced and selection of the correct meaning from among different meanings will be possible.
Example-based Machine Translation, Ontology, Semantic Web
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