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GRAHAM Shawn
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Archaeology specific BERT models for English, German, and Dutch
Multilingual Named Entity Recognition in archaeology: an approach based on deep learning
Recommended by Maria Pia di Buono based on reviews by Shawn Graham and 2 anonymous reviewersArchaeology specific BERT models for English, German, and Dutch” (Brandsen 2024) explores the use of BERT-based models for Named Entity Recognition (NER) in archaeology across three languages: English, German, and Dutch. It introduces six models trained and fine-tuned on archaeological literature, followed by the presentation and evaluation of three models specifically tailored for NER tasks. The focus on multilingualism enhances the applicability of the research, while the meticulous evaluation using standard metrics demonstrates a rigorous methodology.
The introduction of NER for extracting concepts from literature is intriguing, while the provision of a method for others to contribute to BERT model pre-training enhances collaborative research efforts. The innovative use of BERT models to contextualize archaeological data is a notable strength, bridging the gap between digitized information and computational models.
Additionally, the paper's release of fine-tuned models and consideration of environmental implications add further value.
In summary, the paper contributes significantly to the task of NER in archaeology, filling a crucial gap and providing foundational tools for data mining and reevaluating legacy archaeological materials and archives.
Reference
Brandsen, A. (2024). Archaeology specific BERT models for English, German, and Dutch. Zenodo, 8296920, ver. 5 peer-reviewed and recommended by Peer Community in Archaeology. https://doi.org/10.5281/zenodo.8296920