Rajvee Sheth


2024

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Commentator: A Code-mixed Multilingual Text Annotation Framework
Rajvee Sheth | Shubh Nisar | Heenaben Prajapati | Himanshu Beniwal | Mayank Singh
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing: System Demonstrations

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.