Fine-tuning open-source LLMs outperforms prompting for POS tagging on medieval Occitan, French, and Spanish, and pooling Romance training data helps the most under-resourced texts.
Distant Supervision from Disparate Sources for Low-Resource Part-of-Speech Tagging
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abstract
We introduce DsDs: a cross-lingual neural part-of-speech tagger that learns from disparate sources of distant supervision, and realistically scales to hundreds of low-resource languages. The model exploits annotation projection, instance selection, tag dictionaries, morphological lexicons, and distributed representations, all in a uniform framework. The approach is simple, yet surprisingly effective, resulting in a new state of the art without access to any gold annotated data.
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2025 1verdicts
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Unveiling Factors for Enhanced POS Tagging: A Study of Low-Resource Medieval Romance Languages
Fine-tuning open-source LLMs outperforms prompting for POS tagging on medieval Occitan, French, and Spanish, and pooling Romance training data helps the most under-resourced texts.