COMMENTATOR: a code-mixed multilingual text annotation framework

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dc.contributor.author Sheth, Rajvee
dc.contributor.author Nisar, Shubh
dc.contributor.author Prajapati, Heenaben
dc.contributor.author Beniwal, Himanshu
dc.contributor.author Singh, Mayank
dc.coverage.spatial United States of America
dc.date.accessioned 2024-08-14T13:17:23Z
dc.date.available 2024-08-14T13:17:23Z
dc.date.issued 2024-08
dc.identifier.citation Sheth, Rajvee; Nisar, Shubh; Prajapati, Heenaben; Beniwal, Himanshu and Singh, Mayank, "COMMENTATOR: a code-mixed multilingual text annotation framework", arXiv, Cornell University Library, DOI: arXiv:2408.03125, Aug. 2024.
dc.identifier.uri http://arxiv.org/abs/2408.03125
dc.identifier.uri https://repository.iitgn.ac.in/handle/123456789/10340
dc.description.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 \url{this https URL}. The demonstration video is available at \url{this https URL}.
dc.description.statementofresponsibility by Rajvee Sheth, Shubh Nisar, Heenaben Prajapati, Himanshu Beniwal and Mayank Singh
dc.language.iso en_US
dc.publisher Cornell University Library
dc.title COMMENTATOR: a code-mixed multilingual text annotation framework
dc.type Article
dc.relation.journal arXiv


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