# Modern Models, Medieval Texts: A POS Tagging Study of Old Occitan

arXiv: https://arxiv.org/abs/2503.07827 · HTML: https://mlsanity.com/paper/2503.07827/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 10 of its 24 references that are in the map.
- First posted on arXiv 10 Mar 2025.

## Builds on (most cited first, 10 of 10)

- [Qwen2.5 Technical Report](https://mlsanity.com/paper/2412.15115/) (2024)
- [Gemma 2: Improving Open Language Models at a Practical Size](https://mlsanity.com/paper/2408.00118/) (2024)
- [Aya 23: Open Weight Releases to Further Multilingual Progress](https://mlsanity.com/paper/2405.15032/) (2024)
- [Decoding Decoded: Understanding Hyperparameter Effects in Open-Ended Text Generation](https://mlsanity.com/paper/2410.06097/) (2024)
- [Improving Lemmatization of Non-Standard Languages with Joint Learning](https://mlsanity.com/paper/1903.06939/) (2019)
- [Part-of-Speech Tagging on an Endangered Language: a Parallel Griko-Italian Resource](https://mlsanity.com/paper/1806.03757/) (2018)
- [A Grounded Unsupervised Universal Part-of-Speech Tagger for Low-Resource Languages](https://mlsanity.com/paper/1904.05426/) (2019)
- [Weakly Supervised POS Taggers Perform Poorly on Truly Low-Resource Languages](https://mlsanity.com/paper/2004.13305/) (2020)
- [The Best of Both Worlds: Lexical Resources To Improve Low-Resource Part-of-Speech Tagging](https://mlsanity.com/paper/1811.08757/) (2018)
- [Modeling Orthographic Variation in Occitan's Dialects](https://mlsanity.com/paper/2404.19315/) (2024)

## Built on by (most cited first, 2 of 2)

- [Unveiling Factors for Enhanced POS Tagging: A Study of Low-Resource Medieval Romance Languages](https://mlsanity.com/paper/2506.17715/) (2025)
- [Lost in Translation? Exploring the Shift in Grammatical Gender from Latin to Occitan](https://mlsanity.com/paper/2605.09156/) (2026)

## Abstract (arXiv)

Large language models (LLMs) have demonstrated remarkable capabilities in natural language processing, yet their effectiveness in handling historical languages remains largely unexplored. This study examines the performance of open-source LLMs in part-of-speech (POS) tagging for Old Occitan, a historical language characterized by non-standardized orthography and significant diachronic variation. Through comparative analysis of two distinct corpora-hagiographical and medical texts-we evaluate how current models handle the inherent challenges of processing a low-resource historical language. Our findings demonstrate critical limitations in LLM performance when confronted with extreme orthographic and syntactic variability. We provide detailed error analysis and specific recommendations for improving model performance in historical language processing. This research advances our understanding of LLM capabilities in challenging linguistic contexts while offering practical insights for both computational linguistics and historical language studies.