Sheth, RajveeNisar, ShubhPrajapati, HeenabenBeniwal, HimanshuSingh, Mayank2025-08-282025-08-282024-08-01http://arxiv.org/abs/2408.03125http://repository.iitgn.ac.in/handle/IITG2025/19844As 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{this https URL}. The demonstration video is available at \url{this https URL}.en-USe-Printe-Print123456789/435