DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This is Non-Final Office Action in response to application filed on September 11, 2025 in which claims 1-20 are presented for examination.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefore, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea of mental process without significantly more. The claims recite receiving and analyzing database queries; identifying natural language text; determining semantic equivalence between natural-language text; storing an association between natural-language text and query content; and using the stored query content to execute a subsequent query. This judicial exception is not integrated into a practical application because the steps can be performed manually in human mind. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the claim here merely uses the processor as a tool to perform the otherwise mental processes. See October Update at Section I(C)(ii). Thus, the limitations recite concepts that fall into the “mental process” grouping of abstract ideas.
ANALYSIS under Revised Guidance of 2019 PEG:
Statutory Category:
The claims 1-10 are directed to one of the four statutory category (claims 1-8 a device, claim 9 a method or a process, and claim 20 a non-transitory computer readable storage medium).
Step 2A – Prong 1: Is there a Judicial Exception (e.g. abstract idea)? (See MPEP§§2106.04(II)(A)(1), 2106.04(a)(2)).
Claim 1 recites, at its core, the limitations directed to receiving and analyzing database queries; identifying natural language text; determining semantic equivalence between natural-language text; storing an association between natural-language text and query content; and using the stored query content to execute a subsequent query. These steps fall under the abstract idea exception as mental processes and/or methods of organizing human activity. Specifically, limitations such as “determining that the first database query contains a natural language marker and first natural language text,” “determining whether the particular database query content is natively valid,” “storing at least part of the particular database query content in association with at least part of the first natural language text,” “determining that at least part of the second natural language text is semantically equivalent to the at least part of the first natural language text,” “generating second particular database query content using the particular database query content stored in association with the …first natural language text” involve analyzing, comparing, categorizing, and retrieving information. Viewed individually or as an ordered combination, these limitations represent abstract information processing. Although the claim recites a database query processing service, a large language model (LLM), native validity for a particular database query language, and a mechanism that avoids invoking the LLM for semantically equivalent subsequent queries, the invocation of an LLM for queries is recited at a high level of generality. The claim lacks technical detail regarding how these steps are performed beyond using generic computer components. Accordingly, claim 1 recites an abstract idea under step 2A, prong 1.
Step 2A – Prong 2: Is the abstract idea integrated into a practical application? (See MPEP§§2106.04(II)(A)(2), 2106.04(d)). To pass Prong 2, the claim must apply the abstract idea in a meaningful way (e.g., by improving computer functionality or another technology).
Claim 1 recites additional elements such as “a first query containing a natural language marker and natural language text is received,” which amounts to extra solution activity; “the natural language text is provided to an LLM,” which is recited high level of generality; the LLM generates replacement database query content, which is directed to abstract idea of generating replacement query content; “the system determines whether the generated content is natively valid for the database query language;” “the valid query content is execute; “the generated query content is stored in association with the natural language text;” “a second query containing semantically equivalent natural language text is received;” “the system generates second query content using the previously stored query content” and “the second query is executed without using the LLM to generate new natively valid replacement query content”. These elements merely utilize a generic LLM as a generic standard tool. The claimed process fails to provide a specific technical solution, as it relies on conventional caching or associating previously validated query content with corresponding natural language text. Furthermore, the claim does not recite any improvement to computer functionality, data structures, or a specific technological process. Instead, it merely uses a computer as a tool to perform the abstract idea rather than improving the computer itself. Therefore, the claim does not provide meaningful integration into a practical application and fails to meet step 2A, prong 2.
Step 2B: significantly more or amounting to an incentive concept. (See MPEP§2106.05).
Claim 1 recites additional elements, including conventional database query processing service, which provides generic computer processing; a database, which provides conventional data storage; a natural language marker, which involves conventional text processing; a large language model, which is known AI technology; determining native validity, which involves conventional validation; storing query content, which involves conventional database storage or caching; determining semantic equivalence, which involves conventional NLP processing; and executing database queries, which involves conventional database functionality. Thus, the additional elements amount to no more than mere instructions to apply the judicial exception and do not integrate a judicial exception into a practical application or provide an inventive concept. Accordingly, the claim fails under step 2B because the mere implementation on a computer does not provide significantly more.
Dependent claim 2 recites “determining that at least part of the second natural language text is semantically equivalent to the at least part of the first natural language text comprises determining that the at least part of the second natural language text satisfies same constraints as the at least part of the first natural language text” abstract idea under step 2A(i). Therefore, the claimed elements fail to integrate the judicial exception into a practical application.
Dependent claim 3 recites “substituting in one or more variables from the second natural language text that were not present in the first natural language text” abstract idea under step 2A(i). Therefore, the claimed elements fail to integrate the judicial exception into a practical application.
Dependent claim 4 recites “a template that includes one or more placeholders for one or more variables; wherein determining that the at least part of the second natural language text is semantically equivalent to the at least part of the first natural language text comprises determining that the second natural language text matches the template when one or more particular variables from the second natural language text are replaced with the one or more placeholders; and wherein the generating the second particular database query content using the at least part of the particular database query content comprises substituting the one or more placeholders in the template with the one or more particular variables from the second natural language text” abstract idea under step 2A(i). Therefore, the claimed elements fail to integrate the judicial exception into a practical application.
Dependent claim 5 recites “wherein the one or more placeholders are one or more bind variables that refer to one or more memory addresses where one or more actual values for the one or more bind variables are retained” abstract idea under step 2A(ii). Therefore, the claimed elements fail to integrate the judicial exception into a practical application.
Dependent claim 6 recites “generating the at least part of the first natural language text at least in part by removing one or more stop words from the first natural language text before the determining that the at least part of the second natural language text is semantically equivalent to the at least part of the first natural language text” abstract idea under step 2A(i). Therefore, the claimed elements fail to integrate the judicial exception into a practical application.
Dependent claim 7 recites “generating the at least part of the second natural language text at least in part by removing one or more stop words from the second natural language text before the determining that the at least part of the second natural language text is semantically equivalent to the at least part of the first natural language text” abstract idea under step 2A(i). Therefore, the claimed elements fail to integrate the judicial exception into a practical application.
Dependent claim 8 recites “wherein the first database query is received in a database session; wherein the causing execution, by the database query processing service, of an operation responsive to the first database query using the particular database query content comprises returning the particular database query content responsive to the first database query in the database session” abstract idea under step 2A(ii). Therefore, the claimed elements fail to integrate the judicial exception into a practical application.
Dependent claim 9 recites “generating a natural language explanation of the particular database query using the large language model; …returning the natural language explanation of the particular database query content responsive to the first database query in the database session” abstract idea under step 2A(ii). Therefore, the claimed elements fail to integrate the judicial exception into a practical application.
Dependent claim 10 recites “wherein the first database query is received in a database session; wherein the causing execution, by the database query processing service, of an operation responsive to the first database query using the particular database query content comprises causing execution, by the database query processing service, of the first particular database query content to retrieve data from the one or more particular database structures” abstract idea under step 2A(ii). Therefore, the claimed elements fail to integrate the judicial exception into a practical application.
Claim 11 and 16 are rejected due to the similar analysis of claim 1. Claims 12-15 and 17-20 are similar analysis of claims 2-10 and do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element in claims 12-15 and 17-20 represent a further mental process step. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer component, then it falls within the “mental processes” group of abstract ideas. Each additional step is considered an abstract idea (mental process step) and does not integrate the judicial exception into a practical application. An additional abstract idea (mental process step) is not sufficient to amount to significantly more than the judicial exception. Therefore, claims 1-20 are not patent eligible.
Allowable Subject Matter
Claims 1-20 are allowable over the prior art of record. However, they would be allowable if rewritten in a form that overcomes the §101 abstract idea rejections.
The following is an examiner’s statement of reasons for allowance:
Regarding independent claim 1, similar claim 11 and claim 16, the closest art Gandhi et al. (US 20240378399 A1) discloses receiving, by a database query processing service operating on one or more computing devices, a first database query (¶[0025] and [0029]-[0032], Gandhi) comprising one or more commands and one or more conditions (¶[0025] -[0026] and [0037], Gandhi) that are natively valid for a database query language to retrieve data from one or more database structures that are referenced in the first database query (¶[0028]-[0029] and [0051]-[0054], Gandhi) and prompting a particular large language model for natively valid replacement database query content based at least in part on the natural language text in the second database query; based at least in part on the prompting of the particular large language model based at least on the natural language text in the database query (¶[0028]-[0029] and [0051]-[0054], Gandhi). However, the prior art fails to disclose or suggest the claimed provision “accessing particular database query content generated at least in part by the particular large language model responsive to the request; determining whether the particular database query content is natively valid for the database query language to retrieve data from one or more particular database structures that are referenced in the particular database query content; based at least in part on determining that the particular database query content is natively valid for the database query language to retrieve data from the one or more particular database structures that are referenced in the particular database query content, causing execution, by the database query processing service, of an operation responsive to the first database query using the particular database query content; storing at least part of the particular database query content in association with at least part of the first natural language text; accessing, by the database query processing service, a second database query that includes the natural language marker and a second natural language text; determining that at least part of the second natural language text is semantically equivalent to the at least part of the first natural language text; generating second particular database query content using the at least part of the particular database query content stored in association with the at least part of the first natural language text; causing execution, by the database query processing service, of the second particular database query content to retrieve data from the one or more particular database structures without using a large language model to generate natively valid replacement database query content between receiving the second database query and execution of the second particular database query content” as claimed in conjunction with remaining claims provisions.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Sokilov et al. (US 20240303247 A1) disclose systems and methods for writing feedback using an artificial intelligence engine.
Blohm et al. (US 20240346255 A1) disclose contextual knowledge summarization with large language models.
Saligrama Shreeram et al. (US 20250110979 A1) disclose distributed orchestration of natural language tasks using a generate machine learning model.
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/HANH B THAI/Primary Examiner, Art Unit 2163
July 21, 2026
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