Project description
Machine learning for the study of the epigraphic cultures of the ancient Mediterranean
The EU-funded PythiaPlus project will explore the nature of the epigraphic cultures of the Greek and Roman worlds using recent advances in artificial intelligence. Inscriptions offer first-hand evidence for the thought, language, society and history of Antiquity. However, the number and variety of these documents make the study of nuances and shifts across inscriptions a demanding feat. By revolutionising our ability to access and analyse the data through the implementation of machine learning models, PythiaPlus will interpret the epigraphic patterns discovered by these models across the texts and metadata of thousands of Greek and Latin inscriptions, transforming our understanding of epigraphic communication in the ancient Mediterranean.
Objective
PythiaPlus proposes to explore and interpret the nature of the epigraphic cultures of the ancient Mediterranean using Artificial Intelligence. Specifically, it will use Machine Learning (ML) models to trace distinctiveness and change in the Greek and Roman epigraphic evidence on an unprecedented large scale and in unparalleled detail, revealing new insights in linguistic and cultural interactions.
Inscriptions are primary evidence for reconstructing the history and thought of the ancient world, due to their large number and variety in content. However, the chronological development and regional diffusion of inscriptions are not uniform. No print or digital resources exist allowing a precise quantification of inscriptions by time and place, and current approaches are generally confined to specific languages or localised case studies. Recent advances in ML can overcome these limitations: ML is a field of Artificial Intelligence that allows statistical models to discover patterns in large datasets, and learn meaningful representations of them. Because such models can train over vast amounts of data, they can overcome the limitations in quantification and breadth of analysis of current resources and approaches.
By revolutionising our ability to access and analyse the epigraphic data through the implementation of advanced digital technologies, this research will enable and undertake the interpretation of the epigraphic patterns and parallels discovered by ML models across the texts and metadata of thousands of Greek and Latin inscriptions. PythiaPlus will transform our understanding of the use of epigraphic communication and the nature of cultural interference within the written and indirectly spoken languages of the ancient world, making a substantial contribution to the study of Epigraphy and the Historical Sciences.
Fields of science
Keywords
Programme(s)
Funding Scheme
MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)Coordinator
30123 Venezia
Italy