USPTO-LLM: A Large Language Model-Assisted Information-enriched Chemical Reaction Dataset

USPTO-LLM is an information-enriched chemical reaction dataset that provides more side information (reaction conditions and reaction steps division) for developing new reaction prediction and retrosynthesis methods and inspires new problems, such as reaction condition prediction. It comprises over 247K chemical reactions extracted from the patent documents of USPTO (United States Patent and Trademark Office), encompassing abundant information on reaction conditions. 

We employ large language models to expedite the data collection procedures automatically with a reliable quality control process. The extracted chemical reactions are organized as heterogeneous directed graphs, allowing us to formulate a series of prediction tasks, such as reaction prediction, retrosynthesis, and reaction condition prediction, in a unified graph-filling framework.