Within the framework of studies on the councils of the early Church and on the occasion of the anniversary of the Council of Nicaea, the analysis of patristic texts in Greek and Latin continues to pose linguistic and historical challenges, requiring innovative methods to explore the dynamics of reception and interpretation. In this context, the application of advanced Artificial Intelligence techniques to linguistic datasets emerges as a valuable tool for deepening our understanding of an event as momentous as the Council of Nicaea.
Our presentation introduces DamSym, an advanced computational tool developed for retrieving semantically similar sentences in the two languages under examination, with the aim of facilitating the analysis of the transmission and evolution of thematic cores in ancient literature. The first part of the presentation examines the methodology employed in developing the tool, illustrating its architecture and key functionalities, with particular attention to the use of Natural Language Processing (NLP) and Artificial Intelligence techniques to address the linguistic specificities of ancient texts.
In the second part, we present a case study on the Council of Nicaea and the post-conciliar period, highlighting the application of DamSym in analyzing how Nicene theological concepts were received and reinterpreted over the centuries. This approach enables the identification of authors, perspectives, and conceptual cores, going beyond mere verbatim correspondences detectable with traditional Digital Humanities tools.
The objective of this presentation is to demonstrate how the adoption of digital tools can enrich our understanding of the legacy of the councils in Church history, offering new insights into the impact and heritage of these pivotal events.
In the context of early Church council studies and the anniversary of the Council of Nicaea, analyzing Greek and Latin patristic texts presents linguistic and historical challenges. Advanced Artificial Intelligence techniques applied to linguistic datasets offer new insights into the reception and interpretation of such texts.
This presentation introduces DamSym, a computational tool designed to retrieve semantically similar sentences in both languages, aiding the study of thematic transmission and evolution in ancient literature. The first part outlines the tool’s methodology, focusing on its architecture and the use of Natural Language Processing (NLP) and AI to handle ancient text complexities.
A case study on the Council of Nicaea and its aftermath demonstrates DamSym’s application in tracing how Nicene theological concepts evolved over time. By surpassing verbatim matching, this approach identifies authors, perspectives, and conceptual cores. The presentation highlights how digital tools enhance our understanding of Church councils' legacy and impact.