Commentator: A Code-mixed Multilingual Text Annotation Framework
Source
Emnlp 2024 2024 Conference on Empirical Methods in Natural Language Processing Proceedings of System Demonstrations
Date Issued
2024-01-01
Author(s)
Abstract
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 https://github.com/lingo-iitgn/commentator. The demonstration video is available at https://bit.ly/commentator_video.
