Quid est VERITAS? A Modular Framework for Archival Document Analysis
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arXiv
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| Main Authors: | , , , , , |
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| Format: | Preprint |
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2026
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| _version_ | 1866910084774232064 |
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| author | Bassanini, Leonardo Biancardi, Ludovico Ferrara, Alfio Gamberini, Andrea Picascia, Sergio Vaglienti, Folco |
| author_facet | Bassanini, Leonardo Biancardi, Ludovico Ferrara, Alfio Gamberini, Andrea Picascia, Sergio Vaglienti, Folco |
| contents | The digitisation of historical documents has traditionally been conceived as a process limited to character-level transcription, producing flat text that lacks the structural and semantic information necessary for substantive computational analysis. We present VERITAS (Vision-Enhanced Reading, Interpretation, and Transcription of Archival Sources), a modular, model-agnostic framework that reconceptualises digitisation as an integrated workflow encompassing transcription, layout analysis, and semantic enrichment. The pipeline is organised into four stages - Preprocessing, Extraction, Refinement, and Enrichment - and employs a schema-driven architecture that allows researchers to declaratively specify their extraction objectives. We evaluate VERITAS on the critical edition of Bernardino Corio's Storia di Milano, a Renaissance chronicle of over 1,600 pages. Results demonstrate that the pipeline achieves a 67.6% relative reduction in word error rate compared to a commercial OCR baseline, with a threefold reduction in end-to-end processing time when accounting for manual correction. We further illustrate the downstream utility of the pipeline's output by querying the transcribed corpus through a retrieval-augmented generation system, demonstrating its capacity to support historical inquiry. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2603_28108 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Quid est VERITAS? A Modular Framework for Archival Document Analysis Bassanini, Leonardo Biancardi, Ludovico Ferrara, Alfio Gamberini, Andrea Picascia, Sergio Vaglienti, Folco Digital Libraries Artificial Intelligence Information Retrieval The digitisation of historical documents has traditionally been conceived as a process limited to character-level transcription, producing flat text that lacks the structural and semantic information necessary for substantive computational analysis. We present VERITAS (Vision-Enhanced Reading, Interpretation, and Transcription of Archival Sources), a modular, model-agnostic framework that reconceptualises digitisation as an integrated workflow encompassing transcription, layout analysis, and semantic enrichment. The pipeline is organised into four stages - Preprocessing, Extraction, Refinement, and Enrichment - and employs a schema-driven architecture that allows researchers to declaratively specify their extraction objectives. We evaluate VERITAS on the critical edition of Bernardino Corio's Storia di Milano, a Renaissance chronicle of over 1,600 pages. Results demonstrate that the pipeline achieves a 67.6% relative reduction in word error rate compared to a commercial OCR baseline, with a threefold reduction in end-to-end processing time when accounting for manual correction. We further illustrate the downstream utility of the pipeline's output by querying the transcribed corpus through a retrieval-augmented generation system, demonstrating its capacity to support historical inquiry. |
| title | Quid est VERITAS? A Modular Framework for Archival Document Analysis |
| topic | Digital Libraries Artificial Intelligence Information Retrieval |
| url | https://arxiv.org/abs/2603.28108 |