Structured information extraction from scientific text with large language models
Abstract Extracting structured knowledge from scientific text remains a challenging task for machine learning models. Here, we present a simple approach to joint named entity recognition and relation extraction and demonstrate how pretrained large language models (GPT-3, Llama-2) can be fine-tuned t...
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| Autors principals: | , , , , , , , |
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| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
Nature Portfolio
2024-02-01
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| Col·lecció: | Nature Communications |
| Accés en línia: | https://doi.org/10.1038/s41467-024-45563-x |
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