Classics Department - Furman University
GESIS Leibniz Institute for the Social Sciences
Institut für Digital Humanities - Universität zu Köln (University of Cologne)
This paper presents the results in the adaptation of a new workflow of Named Entity Recognition and classification applied to primary sources in Ancient Greek. We used a model of language-independent data extraction and pattern discovery based on machine learning algorithms, which allowed the extraction of a dataset of automatically classified place-names and ethnonyms starting from a small manually annotated dataset. The idea is that we should be able to train the machine to recognize an entity from recurring elements in the context, without providing a long annotated training dataset in advance, working on the assumption that premodern textual sources display a recognized systematicity in their linguistic encoding of space, which provides a test-case for automatic and semi-automatic methods of pattern discovery and extraction.
If this content appears in violation of your intellectual property rights, or you see errors or omissions, please reach out to Scott B. Weingart to discuss removing or amending the materials.
In review
Hosted at Carleton University, Université d'Ottawa (University of Ottawa)
Ottawa, Ontario, Canada
July 20, 2020 - July 25, 2020
475 works by 1078 authors indexed
Conference cancelled due to coronavirus. Online conference held at https://hcommons.org/groups/dh2020/. Data for this conference were initially prepared and cleaned by May Ning.
Conference website: https://dh2020.adho.org/
References: https://dh2020.adho.org/abstracts/
Series: ADHO (15)
Organizers: ADHO