As reaction data can include additional non-textual elements, such as reaction schemes and tables for reporting conditions/yields, multi-modality models will be needed to fully organize unstructured data. For reaction schemes, recent developments in the field of optical chemical structure recognition have enabled open-source tools to accurately capture chemical entities from raster images. Notable examples include MolScribe and RxnScribe developed by Barzilay and coworkers, as well as ReactionDataExtractor by Wilary and Cole. Table parsing/extraction tools have also been developed for chemistry literature, such as the table parsing module in ChemDataExtractor and OpticalTable-SQA , a fine-tuned question-answering language model for table extraction. As multimodal foundation models become increasingly available in fields beyond chemistry, it will be worth exploring their suitability for reaction data extraction.