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spacy-home-nacr-multilingual

Latin
German
Czech
Spacy
Named entity recognition
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  - Spacy v2
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  ---
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- # HOME-NACR Multilingual named entity recognition
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  This model detects Person and Location entities in Latin, Czech and German.
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@@ -29,16 +29,16 @@ The model has been trained using the Spacy v2 library on the HOME-NACR document
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  The model achieves the following results on HOME-NACR:
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  | tag | predicted | matched | Precision | Recall | F1 | Support |
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- | ---- | --------- | ------- | --------- | ------ | ----- | ------- |
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- | PERS | 28276 | 28006 | 0.99 | 0.997 | 0.994 | 28087 |
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- | LOC | 27541 | 27165 | 0.986 | 0.987 | 0.987 | 27528 |
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- | All | 55817 | 55171 | 0.988 | 0.992 | 0.990 | 55615 |
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- ## How to use
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  Please refer to the Spacy library page (https://pypi.org/project/spacy/2.3.2/) to use this model.
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- # Cite us!
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  ```bibtex
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  @inproceedings{10.1007/978-3-031-06555-2_29,
 
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  - Spacy v2
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  ---
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+ # Spacy - HOME-NACR Multilingual
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  This model detects Person and Location entities in Latin, Czech and German.
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  The model achieves the following results on HOME-NACR:
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  | tag | predicted | matched | Precision | Recall | F1 | Support |
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+ | ---- | --------: | ------: | --------: | -----: | ----: | ------: |
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+ | PERS | 28,276 | 28,006 | 0.990 | 0.997 | 0.994 | 28,087 |
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+ | LOC | 27,541 | 27,165 | 0.986 | 0.987 | 0.987 | 27,528 |
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+ | All | 55,817 | 55,171 | 0.988 | 0.992 | 0.990 | 55,615 |
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+ ## How to use?
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  Please refer to the Spacy library page (https://pypi.org/project/spacy/2.3.2/) to use this model.
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+ ## Cite us!
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  ```bibtex
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  @inproceedings{10.1007/978-3-031-06555-2_29,