NER on Ancient Greek texts with minimal annotation

paper, specified "short paper"
  1. 1. Chiara Palladino

    Classics Department - Furman University

  2. 2. Farimah Karimi

    GESIS Leibniz Institute for the Social Sciences

  3. 3. Brigitte Mathiak

    Institut für Digital Humanities - Universität zu Köln (University of Cologne)

Work text
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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.

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Conference Info

In review

ADHO - 2020
"carrefours / intersections"

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 Data for this conference were initially prepared and cleaned by May Ning.

Conference website:


Series: ADHO (15)

Organizers: ADHO