Vidya: An AI-Driven Modular Pipeline for Archival Automation and Semantic Metadata Enrichment
The large-scale digitization of historical archives has created a paradox: "dark data"-digital objects lacking metadata for retrieval. Manual archival description is slow and expensive, limiting discovery and reuse. We propose Vidya, a modular pipeline that orchestrates Large Language Models (LLMs) and FOSS tools to automate semantic enrichment and archival ingestion at scale. Vidya constrains generations using YAML-defined ontologies and Pydantic validation, producing deterministic, structured JSON outputs from probabilistic models. Developed at Laboratory for Digital Humanities and Innovation (LAMUHDI) of the State University of Ponta Grossa (UEPG), Vidya applies Maker principles and op...
| Authors | Cloter Migliorini Filho, Julia Graciela Machado, Edson Armando Silva et al. |
|---|---|
| Primary category | cs.DL |
| Published | 7 May 2026 |
| Last updated at source | 7 May 2026 |
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