Experiments with POS Tagging Code-mixed Indian Social Media Text
October 31, 2016 ยท Declared Dead ยท ๐ 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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