NMRExtractor: leveraging large language models to construct an experimental NMR database from open-source scientific publications

C NMR chemical shifts, data confidence levels, and reference information. Our analysis reveals that NMRBank's chemical space significantly surpasses existing public NMR datasets. The extraction process is highly scalable, allowing automatic processing of new research papers and continuous updates to NMRBank. This approach not only expands the available open NMR data space but also provides a foundation for AI-based NMR predictions and related chemical research. By automating data extraction and creating a comprehensive, regularly updated NMR database, NMRExtractor and NMRBank address the scarcity of publicly available experimental NMR data, potentially accelerating progress in various fields of chemical research.