MUDIDI introduces a two-stage LLM pipeline for multilingual dictionary digitization, releases a human-annotated dataset from 30 dictionaries, and shows LLMs outperforming OCR and VLMs on character recognition, markup, and entry segmentation.
Proceedings of the 28th International Conference on Computational Linguistics , year =
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MUDIDI: A Two-Stage Framework for Multilingual Dictionary Digitization with Language Models
MUDIDI introduces a two-stage LLM pipeline for multilingual dictionary digitization, releases a human-annotated dataset from 30 dictionaries, and shows LLMs outperforming OCR and VLMs on character recognition, markup, and entry segmentation.