EagleW/Chem-FINESE
Official implementation of the EACL Findings 2024 paper: Chem-FINESE: Validating Fine-Grained Few-shot Entity Extraction through Text Reconstruction
Chem-FINESE helps chemical researchers and text data scientists automatically identify and extract specific chemical entities (like names of compounds or reactions) from scientific texts, even with very little example data. You provide raw text documents, and it outputs structured lists of identified chemical entities and their types. This tool is for anyone needing to efficiently organize and analyze information from large volumes of chemistry literature.
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Use this if you need to quickly and accurately extract specific chemical information from scientific papers, patents, or reports, especially when you have limited annotated examples for training.
Not ideal if you're not working with chemical texts or if you require a general-purpose entity extraction tool that isn't specialized for fine-grained chemical entities.
Stars
7
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Language
Python
License
MIT
Category
Last pushed
Mar 18, 2024
Commits (30d)
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