A large number of machine translation approaches has been developed recently with the aim of migrating content easily across languages. However, the literature suggests that many boundaries have to be dealt with to achieve better automatic translations. A central issue that machine translation systems must handle is ambiguity. A promising way of overcoming this problem is using semantic web technologies. This article presents the results of a systematic review of approaches that rely on semantic web technologies within machine translation approaches for translating natural-language sentences. Overall, our survey suggests that while semantic web technologies can enhance the quality of machine translation outputs for various problems, the combination of both is still in its infancy. Machine Translation Using Semantic Web Technologies: A Survey

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