Raveesh Motlani

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In this study, the problem of shallow parsing of Hindi-English code-mixed social media text (CSMT) has been addressed. We have annotated the data, developed a language identifier, a normalizer, a part-of-speech tagger and a shallow parser. To the best of our knowledge, we are the first to attempt shallow parsing on CSMT. The pipeline developed has been made(More)
In this study, the problem of shallow parsing of Hindi-English code-mixed social media text (CSMT) has been addressed. We have annotated the data, developed a language identifier, a normalizer, a part-of-speech tagger and a shallow parser. To the best of our knowledge, we are the first to attempt shallow parsing on CSMT. The pipeline developed has been made(More)
Sindhi, an Indo-Aryan language with more than 75 million native speakers1 is a resourcepoor language in terms of the availability of language technology tools and resources. In this thesis, we discuss the approaches taken to develop resources and tools for a resourcepoor language with special focus on Sindhi. The major contributions of this work include raw(More)
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