NER on Ancient Greek texts with minimal annotation

paper, specified "short paper"
Authorship
  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 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