Data-driven methods are now routinely employed in the physical sciences. A trend toward the use of supervised machine learning (ML) techniques has increased the need for structured data, i.e., data represented using a standardized data schema. In most scientific communities, however, data is stored and communicated predominantly via unstructured documents and prose, with only a few exceptions. 1 Synthetic organic chemistry is no exception. Reaction procedures and details are commonly recorded as free text in journal publications, patents, or electronic lab notebooks (ELNs). Manual information extraction and curation are still widely used to construct structured datasets from unstructured texts. An automated method to extract structured reaction data from unstructured texts would accelerate efforts to use historical reaction data for data-driven discovery.