BiblIndex Beyond Canonical References: Using AI to Map Biblical Text Reuses in Patristic Literature
Résumé
BiblIndex, the online index of biblical text reuses in Early Christian literature, faces three challenges that artificial intelligence could address: the extensive intrabiblical intertextuality requiring many-to-many relationship mapping; the precise delineation of textual reuses beyond canonical verse systems; and establishing a robust typology distinguishing verbatim quotations from distant allusions. Neural language models could identify semantic similarities beyond exact wording, sequence tagging architectures could detect quotation boundaries at character-level precision, and machine learning classifiers could systematically categorize reuse types based on measurable linguistic features. Rather than replacing scholarly expertise, AI would augment human capabilities by processing hundreds of thousands of quotations at scale while maintaining philological rigor, transforming BiblIndex into a dynamic research environment that enables both comprehensive mapping and in-depth study of the textual relationships shaping Christian intellectual history.