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The Patrologia Graeca Corpus: OCR, Annotation, and Open Release of Noisy Nineteenth-Century Polytonic Greek Editions

arXiv cs.CV / 3/11/2026

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Key Points

  • The Patrologia Graeca Corpus is a newly released large-scale OCR and linguistic resource specifically targeting nineteenth-century editions of Ancient Greek texts, which were previously undigitized.
  • The collection deals with complex bilingual Greek-Latin layouts and degraded polytonic Greek typography, presenting significant OCR challenges.
  • By using a pipeline combining YOLO-based layout detection and CRNN-based text recognition, the project achieves a low character error rate of 1.05% and word error rate of 4.69%, outperforming existing OCR systems for polytonic Greek.
  • The corpus includes about six million lemmatized and part-of-speech tagged tokens with full OCR and layout annotations, making it valuable for philology and establishing a benchmark for future polytonic Greek OCR models.
  • The dataset provides important training material for future models, including large language models (LLMs), advancing research in OCR and computational linguistics related to ancient texts.

Computer Science > Computer Vision and Pattern Recognition

arXiv:2603.09470 (cs)
[Submitted on 10 Mar 2026]

Title:The Patrologia Graeca Corpus: OCR, Annotation, and Open Release of Noisy Nineteenth-Century Polytonic Greek Editions

Authors:Chahan Vidal-Gorène (CJM, LIPN), Bastien Kindt
View a PDF of the paper titled The Patrologia Graeca Corpus: OCR, Annotation, and Open Release of Noisy Nineteenth-Century Polytonic Greek Editions, by Chahan Vidal-Gor\`ene (CJM and 2 other authors
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Abstract:We present the Patrologia Graeca Corpus, the first large-scale open OCR and linguistic resource for nineteenthcentury editions of Ancient Greek. The collection covers the remaining undigitized volumes of the Patrologia Graeca (PG), printed in complex bilingual (Greek-Latin) layouts and characterized by highly degraded polytonic Greek typography. Through a dedicated pipeline combining YOLO-based layout detection and CRNN-based text recognition, we achieve a character error rate (CER) of 1.05% and a word error rate (WER) of 4.69%, largely outperforming existing OCR systems for polytonic Greek. The resulting corpus contains around six million lemmatized and part-of-speech tagged tokens, aligned with full OCR and layout annotations. Beyond its philological value, this corpus establishes a new benchmark for OCR on noisy polytonic Greek and provides training material for future models, including LLMs.
Subjects: Computer Vision and Pattern Recognition (cs.CV)
Cite as: arXiv:2603.09470 [cs.CV]
  (or arXiv:2603.09470v1 [cs.CV] for this version)
  https://doi.org/10.48550/arXiv.2603.09470
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arXiv-issued DOI via DataCite
Journal reference: Language Resources and Evaluation Conference, May 2026, Palma De Majorque, Spain

Submission history

From: Chahan Vidal-Gorene [view email] [via CCSD proxy]
[v1] Tue, 10 Mar 2026 10:21:54 UTC (7,365 KB)
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