Experiments with POS Tagging Code-mixed Indian Social Media Text

October 31, 2016 ยท Declared Dead ยท ๐Ÿ› arXiv.org

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Authors Prakash B. Pimpale, Raj Nath Patel arXiv ID 1610.09799 Category cs.CL: Computation & Language Citations 16 Venue arXiv.org Last Checked 4 months ago
Abstract
This paper presents Centre for Development of Advanced Computing Mumbai's (CDACM) submission to the NLP Tools Contest on Part-Of-Speech (POS) Tagging For Code-mixed Indian Social Media Text (POSCMISMT) 2015 (collocated with ICON 2015). We submitted results for Hindi (hi), Bengali (bn), and Telugu (te) languages mixed with English (en). In this paper, we have described our approaches to the POS tagging techniques, we exploited for this task. Machine learning has been used to POS tag the mixed language text. For POS tagging, distributed representations of words in vector space (word2vec) for feature extraction and Log-linear models have been tried. We report our work on all three languages hi, bn, and te mixed with en.
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