Building query context using intermediate queries
AssigneeAmazon Technologies, Inc.
InventorJoshua Kulas
Life of this patent
Estimating the term…
Abstract
A data analytics service receives a question prompt, wherein the prompt requires one or more database format queries to be executed to determine an answer. The data analytics service uses a generative machine learning model to generate an initial database query, which is then executed on data sources associated with the service to retrieve initial results. The data analytics service stores the results of this query in an intermediate storage location, and subsequently, the data analytics service executes intermediate queries to refine and filter the initial retrieved data. The data analytics service generates an updated database query using context derived from results of the intermediate queries, which is used to determine an updated database format query.
Claims20
A system, comprising:
- one or more computing devices comprising one or more processors configured implement a data analytics service, configured to:
- receive an original question prompt which requires SQL queries to be performed to be answered;
- generate, using a generative machine learning model, an initial SQL query to be used in answering the original question prompt;
- perform the initial SQL query on one or more data sources associated with the data analytics service;
- store a result of the SQL query to another storage location of the data analytics service;
- perform one or more intermediate SQL queries on the result of the initial SQL query stored in the other storage location of the data analytics service;
- modify the original question prompt to produce a modified question prompt, wherein the modifications to the original question prompt are based on at least a portion of the results of the one or more intermediate SQL queries and add context to the original question prompt determined using the results of the one or more intermediate SQL queries;
- generate, using the generative machine learning model, an updated SQL query to be used in answering the modified question prompt;
- and
- generate an answer for the original question prompt by performing the updated SQL query on the one or more data sources associated with the data analytics service.
A method, comprising:
- receiving, using a data analytics service, a question prompt which requires database format queries to be performed to be answered;
- generating, using a generative machine learning model, an initial database format query to be used in answering the at least a portion of the original question prompt;
- performing the initial database format query on one or more data sources associated with the data analytics service;
- storing a result of the database format query to another storage location of the data analytics service;
- performing one or more intermediate database format queries on the result of the initial database format query stored in the other storage location of the data analytics service;
- modifying the original question prompt to produce a modified question prompt, wherein the modifications to the original question prompt are based on based on at least a portion of the results of the one or more intermediate database format queries and add context to the original question prompt determined using the results of the one or more intermediate database format queries;
- generating, using the generative machine learning model, an updated database format query to be used in answering the modified question prompt;
- and
- generating an answer for the original question prompt by performing the updated database format query on the one or more data sources associated with the data analytics service.
One or more non-transitory, computer-readable storage media storing program instructions that, when executed on or across one or more computing devices, cause the one or more computing devices to:
- receive, using a data analytics service, a question prompt which requires database format queries to be performed to be answered;
- generate, using a generative machine learning model, an initial database format query to be used in answering the at least a portion of the original question prompt;
- perform the initial database format query on one or more data sources associated with the data analytics service;
- store a result of the database format query to another storage location of the data analytics service;
- perform one or more intermediate database format queries on the result of the initial database format query stored in the other storage location of the data analytics service;
- modify the original question prompt to produce a modified question prompt, wherein the modifications to the original question prompt are based on based on at least a portion of the results of the one or more intermediate database format queries and add context to the original question prompt determined using the results of the one or more intermediate database format queries;
- generate, using the generative machine learning model, an updated database format query to be used in answering the modified question prompt;
- and
- generate an answer for the original question prompt by performing the updated database format query on the one or more data sources associated with the data analytics service.
Dependencies are inferred from the claim text.