Shallow Parsing Pipeline for Hindi-English Code-Mixed Social Media Text
April 11, 2016 ยท Declared Dead ยท ๐ North American Chapter of the Association for Computational Linguistics
"No code URL or promise found in abstract"
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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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