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@@ -27,7 +27,7 @@ Three variants of the model is built with Spacy3 for grant applications.
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  A simple named entity recognition custom model from scratch with annotation tool prodi.gy.
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  Github info: https://github.com/RaThorat/ner_model_prodigy
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  The most general model is 'en_grantss'. The model en_ncv is more suitable to extract entities from narrative CV's.
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- The model en_grant is the most accurate.
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  | Feature | Description |
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  | --- | --- |
 
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  A simple named entity recognition custom model from scratch with annotation tool prodi.gy.
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  Github info: https://github.com/RaThorat/ner_model_prodigy
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  The most general model is 'en_grantss'. The model en_ncv is more suitable to extract entities from narrative CV's.
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+ The model en_grant is the first model in the series.
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  | Feature | Description |
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  | --- | --- |