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# CNER: Concept and Named Entity Recognition
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This is the model card for the NAACL 2024 paper [CNER: Concept and Named Entity Recognition](https://aclanthology.org/2024.naacl-long.461/).
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We fine-tuned a language model (DeBERTa-v3-base) for 1 epoch on our [CNER dataset](https://huggingface.co/datasets/Babelscape/cner)
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The resulting CNER model is able to jointly identifying and classifying concepts and named entities with fine-grained tags.
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**If you use the model, please reference this work in your paper**:
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# CNER: Concept and Named Entity Recognition
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This is the model card for the NAACL 2024 paper [CNER: Concept and Named Entity Recognition](https://aclanthology.org/2024.naacl-long.461/).
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We fine-tuned a language model (DeBERTa-v3-base) for 1 epoch on our [CNER dataset](https://huggingface.co/datasets/Babelscape/cner) using the default hyperparameters, optimizer and architecture of Hugging Face, therefore the results of this model may differ from the ones presented in the paper.
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The resulting CNER model is able to jointly identifying and classifying concepts and named entities with fine-grained tags.
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**If you use the model, please reference this work in your paper**:
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