Abstract: An embodiment generates, using a trained document embedding model, a plurality of table embeddings, each table embedding in the plurality of table embeddings representing a table in a dataset. An embodiment generates, using the trained document embedding model, a query embedding, the query embedding representing a natural language query regarding the dataset. An embodiment identifies a set of responsive tables, the set of responsive tables comprising a first table in the dataset, the first table in the dataset represented by a first table embedding, the first table embedding and the query embedding having a similarity score above a similarity score threshold.