SpaCy
Collection
This collection includes models designed for Named Entity Recognition.
•
3 items
•
Updated
This model detects Person and Location entities in Latin, Czech and German.
The model has been trained using the Spacy v2 library on the HOME-NACR document annotations. The model is compatible with version 2.3.2 of Spacy and incompatible with versions 3.x.x.
The model achieves the following results on HOME-NACR:
tag | predicted | matched | Precision | Recall | F1 | Support |
---|---|---|---|---|---|---|
PERS | 28,276 | 28,006 | 0.990 | 0.997 | 0.994 | 28,087 |
LOC | 27,541 | 27,165 | 0.986 | 0.987 | 0.987 | 27,528 |
All | 55,817 | 55,171 | 0.988 | 0.992 | 0.990 | 55,615 |
Please refer to the Spacy library to use this model.
@inproceedings{spacy2022,
author = {Monroc, Claire Bizon and Miret, Blanche and Bonhomme, Marie-Laurence and Kermorvant, Christopher},
title = {{A Comprehensive Study Of Open-Source Libraries For Named Entity Recognition On Handwritten Historical Documents}},
year = {2022},
isbn = {978-3-031-06554-5},
url = {https://doi.org/10.1007/978-3-031-06555-2_29},
doi = {10.1007/978-3-031-06555-2_29},
booktitle = {Document Analysis Systems: 15th IAPR International Workshop, DAS 2022, La Rochelle, France, May 22–25, 2022, Proceedings},
pages = {429–444},
numpages = {16},
}