Since its original release in 2016, the chemical literature mining toolkit ChemDataExtractor has been continuously developed . The highly adaptable toolkit uses user-defined models of the information to be extracted in a pipeline with readers for different publisher formats and a system for interdependency resolution with a set of parsers and a sophisticated chemical named entity recognition system to extract chemical information in a structured data format . In the past years, ChemDataExtractor has been extensively used to automatically generate databases about refraction indices and dielectric constants [100], battery material properties [101], properties of semiconductors for building solar cells [102], magnetic properties [103], as well as UV/Vis spectra .