This disclosure describes techniques to populate spreadsheet cells that depend on, but aren’t numerically calculable from, other cells. Based on a natural language query, the empty cells of a partially populated sheet that are contextually dependent on the thus-far-filled cells are automatically filled. The techniques provide greater speed, accuracy, and scalability for datasets small and large, enabling users to efficiently explore data. The techniques obviate the need to manually populate each cell in the sheet, a time-consuming and error prone procedure that does not scale well. Automatically filling in values in a spreadsheet, as described herein, opens up possibilities for the user that don’t currently exist, e.g., answering hundreds or thousands of questions based on the context in a sheet using simple, templated, natural-language queries.
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Lavery, Andy; Wagner, Earl J.; and Albright, Matthew, "Automatically Deriving Spreadsheet Cell Values Using Natural Language", Technical Disclosure Commons, (October 12, 2021)