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---
library_name: Spacy
license: mit
tags:
- Spacy
- Named entity recognition
metrics:
- P
- R
- F1
language:
- la
- de
- cs
version:
- Spacy v2
---
# Spacy - HOME-NACR Multilingual
This model detects Person and Location entities in Latin, Czech and German.
## Model description
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.
## Evaluation results
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 |
## How to use?
Please refer to the [Spacy library](https://pypi.org/project/spacy/2.3.5/) to use this model.
## Cite us!
```bibtex
@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title = {{A Comprehensive Study Of Open-Source Libraries For Named Entity Recognition On Handwritten Historical Documents}},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},
}
``` |