Notice of Pre-AIA or AIA Status
The present applicati7410on 18/940,529, filed on 11/7/2024 (or after March 16, 2013), is being examined under the first inventor to file provisions of the AIA (First Inventor to File).
In the event the determination of the status of the application as subject to AIA 35
U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
DETAILED ACTION
Response to Amendment
Claims 1-20 are pending in this application.
Examiner acknowledges applicant’s amendment filed on 6/22/2026
Drawings
The Drawings filed on 11/7/2024 are acceptable for examination purpose.
Response to Arguments
Applicant's arguments filed 6/22/2026 with respect to claims 1-20 have been fully considered but they are not persuasive, for examiner’s response, see discussion below:
35 USC § 101
a)At page 9-12, claim 1, applicant argues:
When a proper "directed to" analysis is applied to the independent claims, it can easily be determined that the present claims are directed to eligible subject matter because they are not directed to any of the ineligible concepts ("judicial exceptions"). The claims are directed to generating follow up queries to a user query based on context provided by the database query representation of the user query. The generation of follow up queries is described throughout the Specification and is embodied in the independent claims with detailed recitation of how to generate the follow up queries to a user query. This determination of what the claims are directed to conforms to the analytical approaches identified by the Federal Circuit when carrying out the Alice/Mayo directed to inquiry.
The claimed follow up query generation based on context provided by a database query representing a user query for which follow up queries are generated is a solution to the problem of recommending generic, existing content to users rather than content directly related to user queries themselves, which is described in the Specification: "While conventional recommendation systems recommend pre-existing content (e.g., videos) to users, such as based on scoring and ranking candidates from existing content, the disclosed follow up query generation service... generates follow up queries to queries submitted by users based on context provided by the corresponding database query representations thereof, follow-up ueries to a user query are provided to the user in a response to the user query.15 Each of the independent claims explicitly recites how to generate the follow ups to a user query, with details of the specific technique for entity extraction and template population to generate the follow up queries,……………. For instance, claim 1 as amended recites extracting one or more entity types from a database query representing a user query, extracting one or more entity names corresponding to the one or more entity types from the database query and/or a result of executing the database query against a target database, and populating each user query template based on the one or more entity names to generate a corresponding follow up query………As stated previously, the advance is the generation of follow up queries to user queries in text-to-database query conversion services based on context provided by database query representations of the user queries, and that sequence is recited in the claims to for a specific "how" for the follow up query generation. Conventional text-to-database query systems do not generate follow up queries for users based on context provided by a database query representation of a user query as the claims recite. Conventional recommendation systems can recommend pre-existing content to users but do not tailor generation of follow ups to a user query to context provided by a database
Examiner’s response:
Examiner submits that the pending claims (as amended 6/22/2026) should pass the test set forth in the 2019 Revised Patent Subject Matter Eligibility Guidance published on January 7, 2019 (84 Fed. Reg. 50), as updated October 2019, referred to herein as the PEG 2019. Applicant will focus on Prong Two of Step 2A, in evaluating the pending claims using this section of the test set forth in the PEG 2019
As explained in the 2019 PEG, the evaluation of Prong Two of Step 2A requires the use of the considerations (e.g. improving technology, effecting a particular treatment or prophylaxis, implementing with a particular machine, etc.) identified by the Supreme Court and the Federal Circuit, to ensure that the claim as a whole “integrates [the] judicial exception into a practical application [that] will apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the judicial exception”. These considerations are set forth in the 2019 PEG, MPEP 2106.05(a) through (c), and MPEP 2106.05(e) through (h). Note, a specific way of achieving a result is not a stand-alone consideration in Step 2A Prong Two. However, the specificity of the claim limitations is relevant to the evaluation of several considerations including the use of a particular machine, particular transformation and whether the limitations are mere instructions to apply an exception. If the claim integrates the judicial exception into a practical application based upon evaluation of these considerations, the additional limitations impose a meaningful limit on the judicial exception, and the claim is eligible at Step 2A.
For example, if the additional limitations as amended 6/22/2025 (generating one or more follow up queries to the first user query based on context provided by the first database query, wherein each of the one or more follow up queries is a follow up to the first user query in natural language………………..generate a corresponding one of the one or more follow up queries………….) do not provide “improvement to another technology or technical field”, for example under broadest reasonable interpretation, cover performance of the limitations , query in natural language….., follow up queries……. Is mental process user/actor that constitute certain methods of organizing human activity but for the recitation of generic computer component(s) and/or general-purpose computer processor to implement the abstract idea. As discussed, the claims as amended (6/22/2026) the broadest reasonable interpretation of above steps is that those steps fall within the mental process grouping of abstract ideas because they cover concepts performed in the human mind, including observation, evaluation, judgement and opinion. See MPEP 2106.04(a)(2).
Taking the claim ,1,13,17 (6/22/2026) elements separately, the functions performed in claim 1,13,17 by the generically recited user query based on context provided by the first database query, wherein each of the one or more follow up queries is a follow up to the first user query in natural language ………………..generate a corresponding one of the one or more follow up queries, add nothing that is not already present when the limitations are considered separately. For example, claim 1,13,17 do not purport to improve the functioning of the follow-up queries in natural language……………Nor does claim 1,13,17 effect an improvement in any other technology or technical field. Instead, claim 1,13,17(as amended 6/22/2026) amounts to nothing significantly more than an instruction to apply the abstract idea using generic computer components performing routine computer functions. That is not enough to transform an abstract idea into a patent-eligible invention. See Alice, 573 US at 225-26; see also Inventor Holdings, LLC v. Bed Bath & Beyond, Inc., 876 F.3d 1372,1378 (Fed.Cir.2017) (sequence of receiving, analyzing, modifying, generating, displaying, and transmitting data recited an abstraction)
Examiner applies above arguments to claims 2-12,14-16,18-20 depend from claim 1,13,17, as such, the pending claims fail Prong Two of Step 2A-2B of the PEG 2019. Therefore, claims 1-20 are rejection under 35 U.S.C. § 101
b)At page, 15, claim 1, applicant argues:
claim 1 is amended to clarify that the follow up query(ies) to the user query is a follow up to the user query that comprises natural language. Claim 1 is also amended to clarify that each follow up query is generated based on populating a user query template(s) based on one or more entity names extracted from a database query corresponding to the user query and/or the database query execution result. Lee/Barkan fails to disclose generating follow ups to a user query in this manner
c)At page. 17-18, claim 13,17, Lee/Barkan does not disclose “generate a plurality of follow up queries to the user query based on context…..follow up user query in natural language
Examiner’s response:
As to the above argument (b-c), the prior art of Lee is directed to receiving natural language input and an SQL template, database software for example performs natural language processing based on text-SQL model (Lee: fig 1, 0018-0019) that including defining templates as detailed in fig 3A, 3B temp1…..temp N, fig 3C, while receiving natural language input from the user(s) as detailed in fig 2 . The prior art of Lee teaches SQL template of user query from subsets selecting and populating based on the natural language input and text values. The prior art of Lee teaches SQL template element 332 for the user input element 302 ie., candidate sets (entities) including tables with plurality of rows corresponding to a columns for SQL templates and text values as natural language inputs to the respective SQL template, query templates corresponds to Lee’s fig 3C-3D SQL template element 332. On the other hand, Chang teaches natural language follow-up queries, particularly relevant follow-up queries in performing analysis, and follow-up queries in the form of question and answer format, for example– Cheng teaches query processing module processes the contextually guided question and answer conversation with the user and generates query results particularly relevance to the user based on the initial query including follow-up queries and/or questions (Chang: fig 2, 0041), therefore, It would have been obvious to a person of ordinary skill in the art at the time of filing the claimed invention natural language embellishment generation and summarization for question-answer system particularly follow-up queries of Chang et al., into one shot learning for text-sql particularly using SQL template based on natural language input of Lee et al., because both Lee, Chang supports natural language queries (Lee: Abstract, fig 2; Chang: Abstract, 0030,0039), and both Lee, Chang supports natural language template (Lee: fig 3, Chang: fig 6), and they both Lee, Chang are from the same field of endeavor. Because both Lee, Chang teaches natural language queries, and template(s), it would have been obvious to one skill ed in the art to substitute and/or modify one method for the other particularly natural language follow-up queries, while maintaining respective template(s) to achieve the predictable interesting patterns, and/or insightful information including statistical analysis to suggest the relevant information (Chang: 0003) thus improves overall quality and reliability of the follow-up queries.
d)At page16-17, claim 1, applicant argues:
The SQL templates in Lee cannot be populated to generate a follow up query comprising natural language as claim 1 recites. The SQL templates are instead populated to generate a SQL query……………. Lee fails to disclose populating a user query template with an entity name(s) to generate a follow up query to a user query, Lee/Barkan cannot disclose all elements of claim 1
Examiner’s response:
As to the above argument (d), the prior art of Lee teaches query templat(s) supporting natural language model (Lee: fig 3A-3C, 0018-0019) defining the object entities such as metadata is integral part of the Lee’s fig 1 as detailed in 0029, further Lee’s fig 3D illustrates query template populated with entities associated with natural language model. On the other hand, Chang teaches in response to the initial query, the response to the follow-up questions associated with the analytics session provided for output to the user using NLG templates associated with analytics session and selected template is filled with specific data i.e, set of data fields element 510, set of data values element 520 corresponds to entities (fig 3, fig 5, 0069-0071)
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Examiner applies above arguments to claims 2-12,14-16,18-20 depend from claim 1,13,17
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 therefor, 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 without significantly more. The judicial exception is not integrated into a practical application.
Claim 1-20 is/are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The judicial exception is not integrated into a practical application. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The eligibility analysis in support of these findings is provided below, in accordance with the 2019 Revised Patent Subject Matter Eligibility Guidance, Federal Register (84 FR 50) on January 7, 2019 hereinafter 2019 PEG
Step 1. In accordance with Step 1 of the eligibility inquiry (as explained in MPEP 2106), it is noted that the method of claim 1,13,17, directed to one of the eligible categories of subject matter and therefore satisfy Step 1.
Step 2A. In accordance with Step 2A prong one of the 2019 PEG, the limitations reciting the abstract idea are highlighted, and the limitations directed to additional elements are highlighted, as set forth in exemplary claim 1
obtaining a first user query comprising natural language and a first database query representing the first user query, wherein the first database query corresponds to a target database;
based on extracting one or more entity types from the first database query, retrieving one or more user query templates from a plurality of user query templates, wherein each of the one or more user query templates comprises one or more parameters corresponding to the one or more entity types;
generating one or more follow up queries to the first user query, based on context provided by the first database query, wherein each of the one or more follow up queries is a follow up to the first user query in natural language, wherein generating the one or more follow up queries based on the context provided by the first database query comprises,
extracting one or more entity names corresponding to the one or more entity types from at least one of the first database query and a result of executing the first database query against the target database; and
populating each of the one or more user query templates based on the one or more entity names to generate a corresponding one of the one or more follow up queries; and
responding to the first user query with a first response comprising the one or more follow up queries”, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. For example, extracting entity types, retrieving query templates, generating queries, extracting entity names, populating templates in the context of this claim encompasses the user thinking mere data gathering
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas set forth in the 2019 PEG. Accordingly, the claim recites an abstract idea.
With respect to Step 2A prong two of the 2019 PEG, the judicial exception is not integrated into a practical application. The additional elements are directed to method steps, however, these elements fail to integrate the abstract idea into a practical application because they fail to provide an improvement to the functioning of a computer or to any other technology or technical field, fail to apply the exception with a particular machine, fail to apply the judicial exception to effect a particular data structure of populating template, extracting entity names and like to effect a transformation of a particular article to a different state or thing, and fail to apply/use the abstract idea in a meaningful way beyond generally linking the use of the judicial exception to a particular technological environment.
Furthermore, although these elements have been fully considered, they are directed to the use of generic computing elements (para: 0071-0076, fig 8 of the instant specification make it clear that the disclosed functionality is implemented on well-known computing systems and general purpose computing devices) to perform the abstract idea, which is not sufficient to amount to a practical application (as noted in the 2019 PEG) and is amount to simply saying "apply it" using a general purpose computer, which merely serves to tie the abstract idea to a particular technological environment computer based operating environment) by using the computer as a tool to perform the abstract idea.
Since the analysis of Step 2A prong one and prong two results in the conclusion that the claims are directed to an abstract idea, additional analysis under Step 2B of the eligibility inquiry must be conducted in order to determine whether any claim element or combination of elements amount to significantly more than the judicial exception.
Step 2B. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The additional method limitations are directed to a generic computer, at a very high level of generality and without imposing meaningful limitations on the scope of the claim. In addition para: 0071-0076, fig 8 of the instant specification describe generic off-the-shelf computer-based elements for implementing the claimed invention which does not amount to significantly more than the abstract idea and is not enough to transform an abstract idea into eligible subject matter. Such generic, high-level, and nominal involvement of a computer or computer-based elements for carrying out the invention merely serves to tie the abstract idea to a particular technological environment, which is not enough to render the claims patent-eligible, as noted at pg. 74624 of Federal Register/Vol. 79, No. 241, citing Alice, which in turn cites Mayo. Further, See, e.g., Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 134 S. Ct. 2347, 2359-60, 110 USPQ2d 1976, 1984 (2014). See also OIP Techs. v. Amazon.com, 788 F.3d 1359, 1364, 115 USPQ2d 1090, 1093-94 (Fed. Cir. 2015) ("Just as Diehr could not save the claims in Alice, which were directed to 'implement[ing] the abstract idea of intermediated settlement on a generic computer', it cannot save O/P's claims directed to implementing the abstract idea of price optimization on a generic computer.") (citations omitted). See also, Affinity Labs of Texas LLC v. DirecTV LLC, 838 F.3d 1253, 1257-1258 (Fed. Cir. 2016) (mere recitation of a GUI does not make a claim patent-eligible); Intellectual Ventures I LLC v. Capital One Bank, 792 F.3d 1363, 1370 (Fed. Cir. 2015) ("the interactive interface limitation is a generic computer element".)
he additional elements are broadly applied to the abstract idea at a high level of generality ("similar to how the recitation of the computer in the claims in Alice amounted to mere instructions to apply the abstract idea of intermediated settlement on a generic computer,") as explained in MPEP § 2106.05(f)) and they operate in a well-understood, routine, and conventional manner.
MPEP § 2106.05 (d)(II) sets forth the following:
The courts have recognized the following computer functions as well-understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g. at a high level of generality) as insignificant extra-solution activity.
Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec...; TLI Communications LLC v. AV Auto. LLC...; OIP Techs., Inc., v. Amazon.com, Inc... ; buySAFE, Inc. v. Google, Inc...;
Performing repetitive calculations, Flook ... ; Bancorp Services v. Sun Life...;
Electronic recordkeeping, Alice Corp...; Ultramercial... ;
Storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc...;
Electronically scanning or extracting data from a physical document, Content Extraction and Transmission, LLC v. Wells Fargo Bank...; and
A web browser's back and forward button functionality, Internet Patent Corp. v. Active Network, Inc...
Courts have held computer-implemented processes not to be significantly more than an abstract idea (and thus ineligible) where the claim as a whole amounts to nothing more than generic computer functions merely used to implement an abstract idea, such as an idea that could be done by a human analog (i.e., by hand or by merely thinking).
Claim 2,14,18 The method of claim 1, further elaborates
“wherein retrieving the one or more user query templates further comprises retrieving a corresponding one or more database query templates,
and
wherein generating the one or more follow up queries further comprises populating parameters of each of the one or more database query templates with the one or more entity names extracted from at least one of the first database query and the result of executing the first database query”, which have been determined to be extra-solution activity that does not impose any meaningful limits on practicing the abstract idea. See MPEP 2106.05(b)(I). Even in combination, the additional details recited in these claims do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea..
Claim 3. The method of claim 1, further elaborates “wherein extracting the one or more entity types from the first database query comprises extracting the one or more entity types from at least one of a first statement in the first database query for selecting data from the target database and a second statement in the first database query for filtering the result obtained from executing the first database query”, which have been determined to be extra-solution activity that does not impose any meaningful limits on practicing the abstract idea. See MPEP 2106.05(b)(I). Even in combination, the additional details recited in these claims do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea..
Claim 4. The method of claim 3, further elaborates “wherein extracting the one or more entity names corresponding to the one or more entity types from at least one of the first database query and the result of executing the first database query against the target database comprises ,
for each of the one or more entity types extracted from the first statement in the first database query, extracting corresponding ones of the one or more entity names from the result obtained from executing the first database query; and
for each of the one or more entity types extracted from the second statement in the first database query, extracting corresponding ones of the one or more entity names from the second statement”, which have been determined to be extra-solution activity that does not impose any meaningful limits on practicing the abstract idea. See MPEP 2106.05(b)(I). Even in combination, the additional details recited in these claims do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea..
Claim 5,15,19 The method of claim 3, further elaborates “wherein the first database query comprises a Structured Query Language (SQL) query, wherein extracting the one or more entity types from at least one of the first statement in the statement in the database query for selecting data from the target database and the second statement in the database query for filtering the result obtained from executing the database query comprises extracting the one or more entity types from at least one of a SELECT statement in the SQL query and a WHERE statement in the SQL query”, which have been determined to be extra-solution activity that does not impose any meaningful limits on practicing the abstract idea. See MPEP 2106.05(b)(I). Even in combination, the additional details recited in these claims do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea..
Claim 6. The method of claim 1, further elaborates “generating a weighted one-hot vector based on the one or more entity types, wherein a vector database maintains a plurality of vectors generated based on the plurality of user query templates, wherein retrieving the one or more query templates comprises querying the vector database with the weighted one-hot vector for one or more of the plurality of vectors most similar to the weighted one-hot vector”, which have been determined to be extra-solution activity that does not impose any meaningful limits on practicing the abstract idea. See MPEP 2106.05(b)(I). Even in combination, the additional details recited in these claims do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea..
Claim 7. The method of claim 1, further elaborates “generating the plurality of user query templates based on a plurality of user queries and a corresponding plurality of database queries, wherein generating the plurality of user query templates comprises, for each user query of the plurality of user queries and corresponding database query from the plurality of database queries,
extracting one or more entity types and names from the database query; and
for each entity type and name of the one or more entity types and names extracted from the database query, determining one or more substrings of the user query to which the entity type and name corresponds and replacing the one or more substrings in the user query with a parameter corresponding to the type of the entity to generate a corresponding one of the plurality of user query templates”, which have been determined to be extra-solution activity that does not impose any meaningful limits on practicing the abstract idea. See MPEP 2106.05(b)(I). Even in combination, the additional details recited in these claims do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea..
claim 8. The method of claim 7, further elaborates “wherein determining the one or more substrings of the user query comprises determining the one or more substrings based on at least one of identifying an exact match between the entity type and name and the one or more substrings, based on fuzzy matching of the entity and the one or more substrings, and based on generating a vector representation of the entity type and name and vector representations of substrings of the user query and determining a most similar one of the vector representations of the substrings of the user query to the vector representation of the entity type and name”, which have been determined to be extra-solution activity that does not impose any meaningful limits on practicing the abstract idea. See MPEP 2106.05(b)(I). Even in combination, the additional details recited in these claims do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea..
claim 9. The method of claim 1, further elaborates “wherein extracting the one or more entity types and extracting the one or more entity names comprises extracting the one or more entity types and the one or more entity names from the first database query based on determining that the result of executing the first database query comprises an empty results set or a value or zero”, which have been determined to be extra-solution activity that does not impose any meaningful limits on practicing the abstract idea. See MPEP 2106.05(b)(I). Even in combination, the additional details recited in these claims do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea..
claim 10. The method of claim 1, further elaborates “based on determining that no entity types and names can be extracted from the first database query, retrieving one or more predefined follow up questions and responding to the first user query with a second response comprising the one or more predefined follow up questions”, which have been determined to be extra-solution activity that does not impose any meaningful limits on practicing the abstract idea. See MPEP 2106.05(b)(I). Even in combination, the additional details recited in these claims do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea..
claim 11. The method of claim 1, further elaborates “wherein the first database query representing the first user query was generated by a first language model based on the first user query, and wherein responding to the first user query comprises prompting a second language model to rephrase each of the one or more follow up queries and responding to the first user query with the rephrased one or more follow up queries”, which have been determined to be extra-solution activity that does not impose any meaningful limits on practicing the abstract idea. See MPEP 2106.05(b)(I). Even in combination, the additional details recited in these claims do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea..
claim 12. The method of claim 1, further elaborates “wherein the first database query indicates a first table of the target database, and wherein each of the one or more user query templates corresponds to the first table of the target database”, which have been determined to be extra-solution activity that does not impose any meaningful limits on practicing the abstract idea. See MPEP 2106.05(b)(I). Even in combination, the additional details recited in these claims do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea..
Claim 16,20. The non-transitory machine-readable media of claim 13, further elaborates
“wherein the instructions to extract the one or more entity types from the database query comprise instructions to extract the one or more entity types from a SQL WHERE statement of the database query,
and wherein the instructions to extract the one or more entity names corresponding to the one or more entity types from the result of executing the database query comprise instructions to extract the one or more entity names from the result of executing the database query”, which have been determined to be extra-solution activity that does not impose any meaningful limits on practicing the abstract idea. See MPEP 2106.05(b)(I). Even in combination, the additional details recited in these claims do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Lee et al., (hereafter Lee), US Pub. No. 2023/0097443 published Mar, 2023 in view of Chang et al., (hereafter Chang), US Pub. No. 2017/0177660 published Jun, 2017
As to Claim 1,13,17. Lee teaches a sys method comprising: (Lee: Abstract)
“obtaining a first user query comprising natural language and a first database query representing the first user query, wherein the first database query corresponds to a database” (Lee: fig 1-2, - Lee teaches text-to-SQL model particularly natural language interface to database; natural language corresponds to fig 2, element 210,220,230 and query language corresponds to element 212,222,232 respectively as detailed in fig 2)
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“based on extracting one or more entity types from the first database query, retrieving one or more user query templates from a plurality of user query templates, wherein each of the one or more user query templates comprises one or more parameters corresponding to the one or more entity types” (Lee: 0029 – Lee teaches data items for example data records, data entries stored in the database element 100 and the database architecture element 100 including metadata defining objects to logical entities and entity types for example country, year, product, state, city, profit, units, sales and like as detailed in 0029; The prior art of Lee teaches query language (SQL) templates paired with respective text values in the predictive network environment (Lee: Abstract), Lee specifically teaches select[ing] SQL template with tokens from the natural language input, in completing the translation of the SQL query (0016, page 2, col 1,0039, fig 3B)
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“generating one or more follow up queries for the first user query, wherein generating the one or more follow up queries comprises” (Lee: fig 2, 0032-Lee teaches generating multiple natural language queries of equivalent respective SQL) ,
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“extracting one or more entity names corresponding to the one or more entity types from at least one of the first database query and a result of executing the first database query against the target database” (Lee: 0032-0033 – Lee teaches retrieving and/or extracting entity names such as “POPULATION”, ‘STATE”; “RIVER”, “Texas”, “Colorado” and like from the natural language input including nested queries and other SQL syntax and in response, the database element 202) and
“populating each of the one or more user query templates based on the one or more entity names”(Lee: Abstract, fig 3C-3D, fig 4, 0048-0049,0056 – Lee teaches SQL template of user query from subsets selecting and populating based on the natural language input and text values. The prior art of Lee teaches SQL template element 332 for the user input element 302 ie., candidate sets (entities) including tables with plurality of rows corresponding to a columns for SQL templates and text values as natural language inputs to the respective SQL template, query templates corresponds to Lee’s fig 3C-3D SQL template element 332)
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; and
“responding to the first user query with a first response comprising the one or more follow up queries” (Lee: fig 2-3, Abstract, 0041 – Lee teaches text-to-SQL generation defining template based model architecture that generates trained templates of SQL with user query response along with training template queries as follow up queries) .
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It is however, noted that Lee does not teach “first database query corresponds to a target database, “wherein each of the one or more follow up queries is a follow up to the first user query in natural language”, one or more entity names to generate a corresponding one of the one or more follow up queries, although Lee teaches text-to-SQL model particularly natural language interface to database (Lee: Abstract, fig 1-2). On the other hand, Chang disclosed “first database query corresponds to a target database” (Chang: Abstract, fig 1,0032,0036 – Chang teaches initial query processing from the client device through network to the server(s) within the distributed environment, further initial query being processed using query processing module and processing query results based on queries via user interface); “wherein each of the one or more follow up queries is a follow up to the first user query in natural language” (Chang: fig 2, 0041 – Cheng teaches query processing module processes the contextually guided question and answer conversation with the user and generates query results particularly relevance to the user based on the initial query including follow-up queries and/or questions.
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The prior art of Chang teaches natural language module to provide first relevant follow-up query from a set of follow-up queries as detailed in fig 9, element 930
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“one or more entity names to generate a corresponding one of the one or more follow up queries” (Chang: fig 3, fig 5, 0069-0071 – Chang teaches in response to the initial query, the response to the follow-up questions associated with the analytics session provided for output to the user using NLG templates associated with analytics session and selected template is filled with specific data i.e, set of data fields element 510, set of data values element 520 corresponds to entities
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It would have been obvious to a person of ordinary skill in the art at the time of filing the claimed invention natural language embellishment generation and summarization for question-answer system particularly follow-up queries of Chang et al., into one shot learning for text-sql particularly using SQL template based on natural language input of Lee et al., because both Lee, Chang supports natural language queries (Lee: Abstract, fig 2; Chang: Abstract, 0030,0039), and both Lee, Chang supports natural language template (Lee: fig 3, Chang: fig 6), and they both Lee, Chang are from the same field of endeavor. Because both Lee, Chang teaches natural language queries, and template(s), it would have been obvious to one skill ed in the art to substitute and/or modify one method for the other particularly natural language follow-up queries, while maintaining respective template(s) to achieve the predictable interesting patterns, and/or insightful information including statistical analysis to suggest the relevant information (Chang: 0003) thus improves overall quality and reliability of the follow-up queries.
As to Claim 2,14,18 , the combination of Lee, Chang disclosed:
“wherein retrieving the one or more user query templates further comprises retrieving a corresponding one or more database query templates” (Lee: fig 3C-3D, 0047)
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“wherein generating the one or more follow up queries further comprises populating parameters of each of the one or more database query templates with the one or more entity names extracted from at least one of the first database query and the result of executing the first database query” (Lee: fig 3C-3D, 0034,0047-0048,0056).
As to Claim 3, the combination of Lee, Chang disclosed ”wherein extracting the one or more entity types from the first database query comprises extracting the one or more entity types from at least one of a first statement in the first database query for selecting data from the database and a second statement in the first database query for filtering the result obtained from executing the first database query” (Lee: fig 2, 0029,0032-0033 - Lee teaches database query including various entity types, also teaches SQL queries in selecting data from the database i.e., database 202 determine a SQL command/query to access data. On the other hand, Chang disclosed “database query for selecting data from the target database” (Chang: 0043, fig 1)
As to Claim 4, the combination of Lee, Chang disclosed “wherein extracting the one or more entity names corresponding to the one or more entity types from at least one of the first database query and the result of executing the first database query against the target database comprises” (Lee: fig 2 – Lee teaches not only entity types, but also SQL query statement) ,
“for each of the one or more entity types extracted from the first statement in the first database query, extracting corresponding ones of the one or more entity names from the result obtained from executing the first database query” (Lee: fig 2, fig 3C – Lee teaches SQL query statement); and
“for each of the one or more entity types extracted from the second statement in the first database query, extracting corresponding ones of the one or more entity names from the second statement” (Lee: fig 2, fig 3C-3D, 0047-0049).
As to Claim 5,15,19, the combination of Lee, Chang disclosed “wherein the first database query comprises a Structured Query Language (SQL) query, (Lee: fig 2 – Lee teaches SQL statement(s)) wherein extracting the one or more entity types from at least one of the first statement in the statement in the database query for selecting data from the target database and the second statement in the database query for filtering the result obtained from executing the database query comprises extracting the one or more entity types from at least one of a SELECT statement in the SQL query and a WHERE statement in the SQL query( Lee: fig 3C-3D, 0047-0049 – Lee teaches SELECT statement in the query corresponds to Lees fig 3D, element 332,340).
As to claim 6, the combination of Lee, Chang disclosed “further comprising generating a weighted one-hot vector based on the one or more entity types, wherein a vector database maintains a plurality of vectors generated based on the plurality of user query templates, (Lee: fig 3B, 0039-0040)wherein retrieving the one or more query templates comprises querying the vector database with the weighted one-hot vector for one or more of the plurality of vectors most similar to the weighted one-hot vector” (Lee: fig 3B, 0039-0040,0043-0044) .
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As to claim 7, the combination of Lee, Chang disclosed “further comprising generating the plurality of user query templates based on a plurality of user queries and a corresponding plurality of database queries, wherein generating the plurality of user query templates comprises, for each user query of the plurality of user queries and corresponding database query from the plurality of database queries” (Lee: fig 3C-3D, 0047)
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“extracting one or more entity types and names from the database query” (Lee: fig 2, 0029,0032-0033; and
“for each entity type and name of the one or more entity types and names extracted from the database query, determining one or more substrings of the user query to which the entity type and name corresponds (Lee: fig 2-3,0032-0033) and replacing the one or more substrings in the user query with a parameter corresponding to the type of the entity to generate a corresponding one of the plurality of user query templates” (Lee: fig 3C-3D)
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As to claim 8, the combination of Lee, Chang disclosed “wherein determining the one or more substrings of the user query comprises determining the one or more substrings based on at least one of identifying an exact match between the entity type and name and the one or more substrings, based on fuzzy matching of the entity and the one or more substrings, (Lee: 0015,0039) and based on generating a vector representation of the entity type and name and vector representations of substrings of the user query and determining a most similar one of the vector representations of the substrings of the user query to the vector representation of the entity type and name” (Lee: fig 3C, 0047-0048).
As to claim 9, the combination of Lee, Chang disclosed “wherein extracting the one or more entity types and extracting the one or more entity names comprises extracting the one or more entity types and the one or more entity names from the first database query based on determining that the result of executing the first database query comprises an empty results set or a value or zero” (Lee: 0039-0040, fig 3B).
As to claim 10, the combination of Lee, Chang disclosed “further comprising, based on determining that no entity types and names can be extracted from the first database query, retrieving one or more predefined follow up questions and responding to the first user query with a second response comprising the one or more predefined follow up questions “ (Lee: fig 2 natural language chat(s); Chang : fig 2, 4, 0045,0048-0049)
As to claim 10, the combination of Lee, Chang disclosed “further comprising, based on determining that no entity types and names can be extracted from the first database query, retrieving one or more predefined follow up questions and responding to the first user query with a second response comprising the one or more predefined follow up questions.“ (Lee: fig 2 natural language chat(s); Chang: fig 8, 0082-0084)
As to claim 11, the combination of Lee, Chang disclosed “wherein the first database query representing the first user query was generated by a first language model based on the first user query, and wherein responding to the first user query comprises prompting a second language model to rephrase each of the one or more follow up queries and responding to the first user query with the rephrased one or more follow up queries” (Chang: 0055,0058,0060,0066, fig 2, 0075,0078).
As to claim 12, the combination of Lee, Chang disclosed “wherein the first database query indicates a first table of the database, and wherein each of the one or more user query templates corresponds to the first table of the database” (Lee: fig 2-3C-3D). On the other hand, Chang disclosed “target database” (Chang: Abstract, fig 1,0032,0036)
As to Claim 16,20, the combination of Lee, Chang disclosed
“wherein the instructions to extract the one or more entity types from the database query comprise instructions to extract the one or more entity types from a SQL WHERE statement of the database query” (Lee: fig 2, element 212,222, 232)
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“and wherein the instructions to extract the one or more entity names corresponding to the one or more entity types from the result of executing the database query comprise instructions to extract the one or more entity names from the result of executing the database query” (Lee: fig 2 – Lee teaches not only entity types, but also SQL query statement).
Conclusion
The prior art made of record
a. US Pub. No. 2023/0097443
b. US Pub. No. 2017/0177660
Examiner's Note: Examiner has cited particular columns and line numbers in the references applied to the claims above for the convenience of the applicant. Although the specified citations are representative of the teachings of the art and are applied to specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested from the applicant in preparing responses, to fully consider the references in entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the Examiner.
SEE MPEP 2141.02 [R-5] VI. PRIOR ART MUST BE CONSIDERED IN ITS ENTIRETY, INCLUDING DISCLOSURES THAT TEACH AWAY FROM THE CLAIMS: A prior art reference must be considered in its entirety, i.e., as a whole, including portions that would lead away from the claimed invention. W.L. Gore & Associates, Inc. v. Garlock, Inc., 721 F.2d 1540, 220 USPQ 303 (Fed. Cir. 1983), cert. denied, 469 U.S. 851 (1984) In re Fulton, 391 F.3d 1195, 1201,73 USPQ2d 1141, 1146 (Fed. Cir. 2004). >See also MPEP §2123.
In the case of amending the Claimed invention, Applicant is respectfully requested to indicate the portion(s) of the specification which dictate(s) the structure relied on for proper interpretation and also to verify and ascertain the metes and bounds of the claimed invention.
The prior art made of record, listed on form PTO-892, and not relied upon, if any, is considered pertinent to applicant's disclosure
Authorization for Internet Communications
The examiner encourages Applicant to submit an authorization to communicate with the examiner via the Internet by making the following statement (from MPEP 502.03):
“Recognizing that Internet communications are not secure, I hereby authorize the USPTO to communicate with the undersigned and practitioners in accordance with 37 CFR 1.33 and 37 CFR 1.34 concerning any subject matter of this application by video conferencing, instant messaging, or electronic mail. I understand that a copy of these communications will be made of record in the application file.”
Please note that the above statement can only be submitted via Central Fax (not Examiner's Fax), Regular postal mail, or EFS Web using PTO/SB/439.
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Srirama Channavajjala whose telephone number is 571-272-4108. The examiner can normally be reached on Monday-Friday from 8:00 AM to 5:30 PM Eastern Time.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Gorney, Boris, can be reached on (571) 270- 5626. The fax phone numbers for the organization where the application or proceeding is assigned is 571-273-8300 Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free)
/Srirama Channavajjala/Primary Examiner, Art Unit 2154
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