Abstract
Machine translation is leading towards a noticeable progress in the era of natural language processing. Started with monolingual, now it’s growing into multilingual translations. Though many devices now come with on the fly translations, the efforts required for low resource languages are incredible. We have developed a system for Indian languages which plays a major role in preserving the context after translation. Like a human, machines are not able to identify and preserve the context, check the dependency between different parts of speech etc. Our contribution is to resolve the anaphora resolution for multilingual, mainly English to Marathi and Hindi translation. Adding the external world knowledge noticeably improves the results for context preservation.
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