Sheth, RajveeRajveeShethNisar, ShubhShubhNisarPrajapati, HeenabenHeenabenPrajapatiBeniwal, HimanshuHimanshuBeniwalSingh, MayankMayankSinghFarias, DIHHope, TLi, M2025-08-282025-08-28[979-8-89176-167-4]https://d8.irins.org/handle/IITG2025/19372As 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 tokenlevel 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.en-USProceedings Paper101-109Proceedings PaperWOS:001511155600011