  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}.
