As the NLP community increasingly addresses challenges associated with multilingualism, robust annotation tools are essential to handle multilingual datasets efficiently. In this paper, we introduce a code-mixed multilingual text annotation framework, COMMENTATOR, specifically designed for annotating code-mixed text. The tool demonstrates its effectiveness in token-level and sentence-level language annotation tasks for Hinglish text. We perform robust qualitative human-based evaluations to showcase COMMENTATOR led to 5x faster annotations than the best baseline. Our code is publicly available at \url{https://github.com/lingo-iitgn/commentator}. The demonstration video is available at \url{https://bit.ly/commentator_video}.
@article{arxiv.2408.03125,
title = {COMMENTATOR: A Code-mixed Multilingual Text Annotation Framework},
author = {Rajvee Sheth and Shubh Nisar and Heenaben Prajapati and Himanshu Beniwal and Mayank Singh},
journal= {arXiv preprint arXiv:2408.03125},
year = {2024}
}