Linking tabular columns to unseen ontologies

A computer system, the computer system comprising:

• one or more processors, one or more computer-readable memories, one or more computer-readable tangible storage medium, and program instructions stored on at least one of the one or more computer-readable tangible storage medium for execution by at least one of the one or more processors via at least one of the one or more computer-readable memories, wherein the computer system is capable of performing a method comprising:
• for a target table, encoding a target tabular query column, table headers, and target types independently to generate permutation invariant representations of type data associated with a target ontology and tabular data associated with the target table, wherein encoding the target types further includes encoding associated auxiliary information, wherein the auxiliary information includes a partial taxonomy structure comprising linearized two-hop is-a ancestor labels;
• processing the encoded tabular query column using a first transformer to obtain a first vector and the encoded table headers using a second transformer to obtain a second vector;
• concatenating the first vector and the second vector to obtain a combined vector;
• processing the combined vector through a linear layer and a Gaussian Error Linear Unit layer to obtain a final query vector;
• processing the encoded target types through a third transformer to obtain a third vector;
• and
• calculating a score for the target tabular query column as a dot product between the final query vector and the third vector to model interactions between the target tabular query column of the target table and the target types and provide a column-type annotation.

A computer program product, the computer program product comprising:

• one or more computer-readable storage medium and program instructions stored on at least one of the one or more computer-readable storage medium, the program instructions executable by a processor capable of performing a method, the method comprising:
• for a target table, encoding a target tabular query column, table headers, and target types independently to generate permutation invariant representations of type data associated with a target ontology and tabular data associated with the target table, wherein encoding the target types further includes encoding associated auxiliary information, wherein the auxiliary information includes a partial taxonomy structure comprising linearized two-hop is-a ancestor labels;
• processing the encoded tabular query column using a first transformer to obtain a first vector and the encoded table headers using a second transformer to obtain a second vector;
• concatenating the first vector and the second vector to obtain a combined vector;
• processing the combined vector through a linear layer and a Gaussian Error Linear Unit layer to obtain a final query vector;
• processing the encoded target types through a third transformer to obtain a third vector;
• and
• calculating a score for the target tabular query column as a dot product between the final query vector and the third vector to model interactions between the target tabular query column of the target table and the target types and provide a column-type annotation.