A CRF Based POS Tagger for Code-mixed Indian Social Media Text
Abstract
In this work, we describe a conditional random fields (CRF) based system for Part-Of- Speech (POS) tagging of code-mixed Indian social media text as part of our participation in the tool contest on POS tagging for codemixed Indian social media text, held in conjunction with the 2016 International Conference on Natural Language Processing, IIT(BHU), India. We participated only in constrained mode contest for all three language pairs, Bengali-English, Hindi-English and Telegu-English. Our system achieves the overall average F1 score of 79.99, which is the highest overall average F1 score among all 16 systems participated in constrained mode contest.
Keywords
Cite
@article{arxiv.1612.07956,
title = {A CRF Based POS Tagger for Code-mixed Indian Social Media Text},
author = {Kamal Sarkar},
journal= {arXiv preprint arXiv:1612.07956},
year = {2016}
}
Comments
This work is awarded the first prize in the NLP tool contest on "POS Tagging for Code-Mixed Indian Social Media Text", held in conjunction with the 13th International Conference on Natural Language Processing 2016(ICON 2016), Indian Institute of Technology (BHU), India