SOTAVerified

Chemical Entity Recognition

Chemical Entity Recognition (CER) is a fundamental task in biomedical text mining and Natural Language Processing (NLP). It involves the identification and classification of chemical entities in textual data, such as scientific literature. These entities can encompass a broad range of concepts including chemical compounds, drugs, elements, ions or functional groups. Given the complexity and variety of chemical nomenclature, the CER task represents a significant challenge for LLMs, and their performance in this task can provide important insights into their overall capabilities in the biomedical domain.

Papers

Showing 13 of 3 papers

TitleStatusHype
Chem-FINESE: Validating Fine-Grained Few-shot Entity Extraction through Text ReconstructionCode0
Mol-Instructions: A Large-Scale Biomolecular Instruction Dataset for Large Language ModelsCode2
The overview of the NLM-Chem BioCreative VII track: full-text chemical identification and indexing in PubMed articles0
Show:102550

No leaderboard results yet.