Shallow Parsing Pipeline for Hindi-English Code-Mixed Social Media Text

April 11, 2016 ยท Declared Dead ยท ๐Ÿ› North American Chapter of the Association for Computational Linguistics

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Authors Arnav Sharma, Sakshi Gupta, Raveesh Motlani, Piyush Bansal, Manish Srivastava, Radhika Mamidi, Dipti M. Sharma arXiv ID 1604.03136 Category cs.CL: Computation & Language Citations 84 Venue North American Chapter of the Association for Computational Linguistics Last Checked 3 months ago
Abstract
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 available to the research community with the goal of enabling better text analysis of Hindi English CSMT. The pipeline is accessible at http://bit.ly/csmt-parser-api .
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