Sheth, RajveeRajveeShethNisar, ShubhShubhNisarPrajapati, HeenabenHeenabenPrajapatiBeniwal, HimanshuHimanshuBeniwalSingh, MayankMayankSingh2025-08-312025-08-312024-01-01[9798891761674]10.18653/v1/2024.emnlp-demo.112-s2.0-85216571870http://repository.iitgn.ac.in/handle/IITG2025/28482As 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 https://github.com/lingo-iitgn/commentator. The demonstration video is available at https://bit.ly/commentator_video.falseConference Paper101-10920240cpConference Proceeding0