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Ohio State University (Columbus, OH 43210-1132)
Brian Daniel Joseph (Project Director: January 2017 to present)
Christopher Brown (Co Project Director: May 2017 to present)
Micha Elsner (Co Project Director: May 2017 to present)
Marie-Catherine de Marneffe (Co Project Director: May 2017 to present)
Named Entity Recognition For The Classical Languages For The Building Of A Catalog Of Ancient Peoples

The creation of a catalog of individuals and groups of individuals mentioned in ancient sources, in part to focus attention on the historical role played by those other than the “great actors” (the important individuals, states, or empires singled out in historic texts). To do so, they will use Named Entity Recognition, a computational linguistics method which identifies people and place names in texts and then sorts them into pre-defined categories, allowing further study and analysis.

The Herodotos Project is creating a catalog of all groups of peoples mentioned in ancient sources, ultimately to assemble informational material for a detailed ethnohistoric profile of each. Our sources at first are Latin and Greek texts. Given the labor-intensive and time-consuming nature of manually searching texts in the original language, and for greater accuracy, we are automating the group name extraction process, drawing on Named Entity Recognition (NER) technology from computational linguistics to identify significant entities in a given text, including our target group names. Most NER systems are English-based, so we have been creating a Latin system that is successful (c. 90% accuracy) but needs more development to achieve even better results. Also, we must adapt our Latin-based system for use with Greek. The NER-development phase of the Project is an essential step towards furthering the creation of the catalogue that will fuel the ethnohistoric side of the overall project.

[Grant products]

Project fields:
Ancient History; Classical Languages; Computational Linguistics

Digital Humanities Advancement Grants

Digital Humanities

$74,808 (approved)
$74,808 (awarded)

Grant period:
10/1/2017 – 8/31/2020