Euporia: rituals in ancient Greek tragedy

Euporia Rituals in ancient Greek Tragedy (RAGT) is an ongoing project for the creation of a browsable database of rituals and religious facts in ancient Greek tragedy. The project is the result of the cooperation between the Laboratorio di Antropologia del Mondo Antico (LAMA) at the University of Pisa and the Collaborative Philology Lab of the Institute of Computational Linguistics “A. Zampolli” at the CNR of Pisa.

The annotation and the querying system were developed in order to offer digital support to Gloria Mugelli’s PHD Thesis, an historical anthropological research on the form and function of rituals in ancient Greek tragedy.

The results (database, tagset, ontology and search interface) are aimed to be published in open access.

The project involved two stages:

  • the annotation of ritual and religious facts in the corpus of the 33 surviving ancient Greek tragedies, carried out with an annotation system based on the annotation practices of classicists, that allows the user to quote continuous and discontinuous passages of various length and deals with textual and interpretive variants. The quoted passages were annotated with keywords expressed as hashtags.
  • the organisation of the tagset in an ontology and the development of a system to perform complex and expressive queries on the database, carried out adopting a bottom-up approach: a search engine (EuporiaSearch) was developed in order to perform queries on the database of the annotated passages. The tagset has been subsequently organized in an ontology, that establishes relations between the different keywords used in the annotation. A system for querying the database, using the ontology in order to perform more complex and expressive queries, is under construction.

Further readings


EuporiaSearch – the prototype version of the search engine, with instruction for a demo query, are published on



Gloria Mugelli, Andrea Taddei – LAMA

Federico Boschetti, Andrea Bellandi, Riccardo Del Gratta, Angelo Mario Del Grosso, Fahad Khan – CoPhiLab, ILC CNR Pisa