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A CRF Based POS Tagger for Code-mixed Indian Social Media Text

  • arXiv (Cornell University)
  • Cornell University
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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.

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Publication details

DOI
10.48550/arxiv.1612.07956
OpenAlex
W2561250218
Document type
preprint
Language
EN
Source
arXiv (Cornell University)
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