# TRIDIS: A Comprehensive Medieval and Early Modern Corpus for HTR and NER

arXiv: https://arxiv.org/abs/2503.22714 · HTML: https://mlsanity.com/paper/2503.22714/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 21 references that are in the map.
- First posted on arXiv 25 Mar 2025.

## Builds on (most cited first, 2 of 2)

- [MiniCPM-V: A GPT-4V Level MLLM on Your Phone](https://mlsanity.com/paper/2408.01800/) (2024)
- [TrOCR: Transformer-based Optical Character Recognition with Pre-trained Models](https://mlsanity.com/paper/2109.10282/) (2021)

## Built on by (most cited first, 3 of 3)

- [Democratizing the medieval English legal tradition](https://mlsanity.com/paper/2605.00977/) (2026)
- [TrOCR for Medieval HTR: A Systematic Ablation Study with Cross-Dataset Validation](https://mlsanity.com/paper/2606.24302/) (2026)
- [When Simpler Is Better: Evaluating Translation Pipelines for Medieval Latin Manuscripts](https://mlsanity.com/paper/2607.03836/) (2026)

## Abstract (arXiv)

This paper introduces TRIDIS (Tria Digita Scribunt), an open-source corpus of medieval and early modern manuscripts. TRIDIS aggregates multiple legacy collections (all published under open licenses) and incorporates large metadata descriptions. While prior publications referenced some portions of this corpus, here we provide a unified overview with a stronger focus on its constitution. We describe (i) the narrative, chronological, and editorial background of each major sub-corpus, (ii) its semi-diplomatic transcription rules (expansion, normalization, punctuation), (iii) a strategy for challenging out-of-domain test splits driven by outlier detection in a joint embedding space, and (iv) preliminary baseline experiments using TrOCR and MiniCPM2.5 comparing random and outlier-based test partitions. Overall, TRIDIS is designed to stimulate joint robust Handwritten Text Recognition (HTR) and Named Entity Recognition (NER) research across medieval and early modern textual heritage.