NER on Ancient Greek with minimal annotation. Palladino, C., Karimi, F., & Mathiak, B. In https://dh2020.adho.org/, 2020. DH2020.
Paper doi abstract bibtex This paper presents the results in the adaptation of a new workflow of Named Entity Recognition and classification applied to Ancient Greek. We used a model of data extraction and pattern discovery based on machine learning algorithms which is easily customizable for different languages. This allowed the creation of a dataset of automatically classified place-names and ethnonyms starting from a small manually annotated list. We worked on the assumption that premodern textual sources display a recognized systematicity in their linguistic encoding of space, which provides a test-case for automatic context-based methods. 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 large training dataset in advance.
@inproceedings{palladino_ner_2020,
title = {{NER} on {Ancient} {Greek} with minimal annotation},
url = {https://works.hcommons.org/records/wv2mz-m9p64},
doi = {10.17613/j7jt-b052},
abstract = {This paper presents the results in the adaptation of a new workflow of Named Entity Recognition and classification applied to Ancient Greek. We used a model of data extraction and pattern discovery based on machine learning algorithms which is easily customizable for different languages. This allowed the creation of a dataset of automatically classified place-names and ethnonyms starting from a small manually annotated list. We worked on the assumption that premodern textual sources display a recognized systematicity in their linguistic encoding of space, which provides a test-case for automatic context-based methods. 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 large training dataset in advance.},
language = {en},
urldate = {2025-06-17},
booktitle = {https://dh2020.adho.org/},
publisher = {DH2020},
author = {Palladino, Chiara and Karimi, Farimah and Mathiak, Brigitte},
year = {2020},
}
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