System, method, and computer program for converting a natural language query to a nested database query

Abstract

The present disclosure describes a system, method, and computer program for converting natural language queries to structured database queries, including nested database queries. In response to receiving a natural language query for a database, an NLU model is applied to the query to identify an intent and entities associated with the query. The entities are tagged with an entity type that enables the system to identify any database object names, candidate query fields, operands, and contextual entities in the query. From the tagged entities, the system identifies one or more valid explicit, implicit, and indirect references to database objects in the user query. If there is only one valid reference to a database object in the user's query, the system proceeds with steps to create a single-object query. If there are valid references to two or more database objects in the query, the system proceeds with steps to create a nested database query. This includes grouping candidate query fields, operands, and contextual entities by independent object name, and evaluating each group separately to identify subject fields, conditional parameters, order/sort criteria, and record count limits for each group.