Chemical patents are a commonly used channel for disclosing novel compounds and reactions, and hence represent important resources for chemical and pharmaceutical research. Key chemical data in patents is often presented in tables. Both the number and the size of the tables can be very large in patent documents. In addition, various types of information can be presented in tables in patents, including spectroscopic and physical data, or pharmacological use and effects of chemicals. Categorisation of tables based on the nature of their content can help to support finding tables containing key information, improving the accessibility of information in patents that is highly relevant for new inventions. To enable the research on methods for automatic table categorization, we developed a new dataset, called ChemTables, which consists of 7,886 chemical patent tables with labels of their content type. This sample is 10% of the created ChemTables dataset. We also provide a stratified 60:20:20 split for train/dev/test set here, which can be used as a standard split for evaluating methods on table categorization task on this dataset.
|Date made available||Nov 4 2020|