Notice of Pre-AIA or AIA Status
The present application 19/074,205, filed on 3/7/2025 (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
Claims 1-20 are pending in this application.
Drawings
The Drawings filed on 3/7/2025 are acceptable for examination purpose.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 11/24/2025 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner
Priority
Acknowledgment is made of applicant’s claim for domestic priority application
U.S. Provisional Patent application serial number # 63/562,610 filed 03/07/2024
under 35 U.S.C. 119 (e)
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 1,3-5,7-11,15,18,19-20 is/are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
As to claim 1,4-5,7-11,15,18,19-20, it is unclear what is meant by “relevant verified statements”, particularly “relevant verified” is a relative term which renders the claim indefinite. The term “relevant” of the verified statements is not defined by the claim, the specification does not provide a standard for ascertaining the requisite “relevant” and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention.
As to claims 3-4,17-18, it is unclear what is meant by “most relevant to the query………….”, the term “most relevant”, is a relative term which renders the claim indefinite, and is not defined by the claim, the specification does not provide a standard for ascertaining the requisite “most relevant”, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention.
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.
Claim 20 is 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 20 is directed to “One or more computer-readable storage media storing instructions that when executed by one or more computers cause the one or more computers to perform operations comprising” is rejected under 35 U.S.C. 101 because the claimed invention is directed to non- statutory subject matter, because in view of specification (page 19-20), “computer-readable storage media storing instructions” is limited to a non-transitory medium or transitory electromagnetic signal and claim 20, under the broadest reasonable interpretation “computer-readable storage media” is considered to read on a transitory propagating signal such as “transmitted signal”, “electromagnetic signal”(spec: page 20, line 5-7)
See the Subject Matter Eligibility of Computer Readable Media memo dated February, 23 2010 (1351 OG 212).
Spec: page 20, line 5-7:
(the storage medium can be storage device………Additiionally or alternatively, the program instructions can be encoded on a transmitted signal, such as a machine-generated electrical, optical, or electromagnetic signal……………………………)
The examiner suggests amending the claim 20 to cover only statutory embodiments by adding the limitation "non-transitory" to the claim 20
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 1,9,15, 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
Claim 1,15,20.
receiving a query comprising natural language text for verification;
obtaining, from a set of text segments, a subset of relevant text segments that are relevant to the query;
obtaining, from a current set of verified statements, a subset of relevant verified statements that are relevant to the query;
generating, using a query verifier machine learning model, a prediction of whether the query is valid given the relevant text segments and the relevant verified statements; and
determining whether to update the current set of verified statements to include the query based on the prediction of whether the query is valid”, 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, receiving query, obtaining text segments, verify[ed] statements, generating, determine whether to update and like, this limitation encompasses the user thinking of data collection, update
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 query natural language text, verified statements, generating using query 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 (page 18-21, 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 page 18-21 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".)
The 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, 16, further elaborates “wherein determining whether to update the current set of verified statements to include the query based on the prediction of whether the query is valid comprises:
determining that the prediction indicates that the query is valid, wherein the prediction includes a confidence score; and
in response to the confidence score meeting a threshold, updating the current set of verified statements to include the 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 3,17, further elaborates “wherein obtaining, from a set of text segments, a subset of relevant text segments that are relevant to the query comprises:
providing the query and the set of text segments as input to a text segment retriever machine learning model that is configured to generate an output that identifies a subset of relevant text segments from the set of text segments that are most relevant to the 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 4,18, further elaborates “wherein obtaining, from a current set of verified statements, a subset of relevant verified statements that are relevant to the query comprises:
providing the query and the current set of verified statements as input to a statement retriever machine learning model that is configured to generate an output that identifies a subset of relevant verified statements from the current set of verified statements that are most relevant to the 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 5,19, further elaborates “wherein the query verifier machine learning model is configured to:
for each relevant text segment, process the query concatenated with the relevant text segment to generate a respective encoding for the relevant text segment;
for each relevant verified statement, process the query concatenated with the relevant verified statement to generate a respective encoding for the relevant verified statement;
generate a decoder input from the respective encodings for the relevant text segments and the respective encodings for the relevant verified statements; and
process the decoder input using a decoder to generate an output token representing the prediction of whether the query is valid”, 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, further elaborates “wherein the current set of verified statements is determined by:
for each of a plurality of initial queries:
obtaining, from the set of text segments, a respective subset of relevant text segments that are relevant to the initial query;
generating a respective prediction for the initial query of whether the initial query is valid by processing the initial query and the respective subset of relevant text segments using a first neural network;
identifying respective predictions for the initial queries that indicate that the initial query is valid;
obtaining a respective confidence for each of the identified respective predictions; and
initializing the current set of verified statements to include initial queries from the plurality of initial queries for which the respective confidence for the identified respective prediction meets a confidence threshold”, 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, further elaborates
“for each of the plurality of initial queries:
obtaining, from the current set of verified statements, a respective subset of relevant verified statements that are relevant to the initial query.
Claim 8, “wherein obtaining, from a current set of verified statements, a subset of relevant verified statements that are relevant to the query comprises providing the query and the current set of verified statements as input to a statement retriever machine learning model that is configured to generate an output that identifies a subset of relevant verified statements from the current set of verified statements that are most relevant to the query, and wherein obtaining, from the current set of verified statements, a respective subset of relevant verified statements that are relevant to the initial query comprises providing the initial query and the current set of verified statements as input to the statement retriever machine learning model”, 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, further elaborates
“for each of a plurality of iterations:
increasing the confidence threshold;
for each of the plurality of initial queries:
generating a respective updated prediction for the initial query by processing the initial query, the respective subset of relevant text segments for the initial query, and the respective subset of relevant verified statements for the initial query using the query verifier machine learning model;
identifying respective updated predictions for the initial queries that indicate that the initial query is valid;
obtaining a respective confidence for each of the identified respective updated predictions;
updating the current set of verified statements to include initial queries from the plurality of initial queries for which the respective confidence for the identified respective updated prediction meets the confidence threshold; and
for each of the plurality of initial queries:
updating the respective subset of relevant verified statements for the initial 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 10, further elaborates “wherein obtaining, from a current set of verified statements, a subset of relevant verified statements that are relevant to the query comprises providing the query and the current set of verified statements as input to a statement retriever machine learning model that is configured to generate an output that identifies a subset of relevant verified statements from the current set of verified statements that are most relevant to the query, and wherein updating the respective subset of relevant verified statements for the initial query comprises providing the initial query and the current set of verified statements as input to the statement retriever machine learning model”, 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, further elaborates
“for each of the plurality of initial queries:
generating a respective second updated prediction for the initial query by processing the initial query, the respective subset of relevant text segments for the initial query, and the respective subset of relevant verified statements for the initial query using the query verifier machine learning model”, 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, further elaborates
“updating the current set of verified statements to include initial queries from the plurality of initial queries for which the respective second updated prediction indicates that the initial query is valid”, 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 13, further elaborates “wherein at least a subset of the plurality of initial queries is obtained from a user”, 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 14, further elaborates “wherein the first neural network is configured to:
for each relevant text segment, process the initial query concatenated with the relevant text segment to generate a respective encoding for the relevant text segment;
generate a decoder input from the respective encodings for the relevant text segments; and
process the decoder input using a first decoder to generate an output token representing the prediction of whether the initial query is valid”, 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 1-4, 6-13,15-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Curtis et al., (hereafter Curtis), US Patent No. 12,511,281 based on provisional application filed on Mar,2022 in view of Cucerzan et al., (hereafter Cucerzan), US Pub. No. 2013/0268519 published Oct, 2013
As to Claim 1,15,20, Curtis teaches a system which including A method comprising: (Curtis: Abstract).
“receiving a query comprising natural language text” (Curtis: Abstract, fig 5A-5B, col 13, line 66-67, col 14, line 1-5, fig 7, element 702, col 14, line 62-67 – Curtis teaches natural language text query as shown in fig 5A-5B, fig 7)
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“obtaining, from a set of text segments, a subset of relevant text segments that are relevant to the query” (Curtis: col 10, line 1-21, fig 2, col 26, line 5-35 - Curtis teaches source data processing into data events, referred as “segment” of the data, and the parsing module extracts data from the events, further event data to the indexing module element 936 that performs event segmentation forms data structure, also it is noted that event segmentation identifies searchable segments including subsets of respective data segments corresponds to text segments);
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obtaining, from a current set of statements, a subset of relevant statements that are relevant to the query” (Curtis: fig 2, fig 3B, col 10, line 21-25, line 35-43, - Curtis teaches plurality of search query statements element 220 i.e, including subset of relevant query statements);
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“generating, using a query machine learning model, a prediction of whether the query is given the relevant text segments and the relevant statements” (Curtis: col 3, line 1-6, line 24-28, fig 7, col 15, line 11-52, – Curtis teaches generat[ing] search query statements from the natural language as input to a trained machine learning model, also prior art of Curtis teaches artificial intelligence or generative AI used operations of training machine learning model to predict a text output such as natural language text, further machine learning model is trained to predict one or more executable search query statements); and
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“determining whether to update the current set of statements to include the query based on the prediction of whether the query” (Curtis: col 4, line 31-36, col 8, line 22-26, col 15, line 45-52, fig 7, element 710 – Curtis teaches update the search query statements).
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It is however, noted that Curtis does not teach “query verification”, although Curtis teaches query (Curtis: Abstract). On the other hand, “query verification” (Cucerzan: fig 1, 0022-0023 – Cucerzan teaches verification engine that provide search queries in the form of statements and/or natural language statements)
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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 verification engine that supports input statement particularly verification engine is trained to receive input statements of Curcerzan et al., into natural language queries into search query statements of Curtis et al., because that would have allowed users of Curtis to verify search queries particularly in the trained machine learning model thereby verification engine of Curcerzan include configuring to rewrite the input statement to get respective expected query output (Curcerzan: 0004-0005), as such both Curtis, Curcerzan specifically supports natural language query, training machine learning model (Curtis: Abstract, fig 5A-5B; Curcerzan: fig 2), and they both are from the same field of endeavor, thus improves overall quality and reliability of the system
As to Claim 2, 16, the combination of Curtis, Curcerzan disclosed:
“determining that the prediction indicates that the query, wherein the prediction includes a confidence score” (Curtis: col 4, line 31-39, col 8, line 21-29, col 13, line 17-26, col 15, line 34-41, fig 7) ; and
“in response to the confidence score meeting a threshold, updating the current set of statements to include the query” (Curtis: col 13, line 17-26, col 15, line 34-41, fig 7). On the other hand, Curcerzan disclosed “query valid, verified statements to include the query” (Curcerzan: fig 1,0014, 0021-0022 – query engine is configured to detect queries and providing thee queries to the verification engine)
As to Claim 3,17, the combination of Curtis, Curcerzan disclosed:
“providing the query and the set of text segments as input to a text segment retriever machine learning model that is configured to generate an output that identifies a subset of relevant text segments from the set of text segments that are most relevant to the query” (Curtis: col 3, line 1-6, line 24-28, col 4, line 31-39, col 7, line 44-54, col 26, line 24-45) .
As to Claim 4,18, the combination of Curtis, Curcerzan disclosed:
“providing the query and the current set of statements as input to a statement retriever machine learning model that is configured to generate an output that identifies a subset of relevant verified statements from the current set of statements that are most relevant to the query” (Curtis : col 4, line 31-39, col 7, line 44-54, col 8, line 56-61,col 11, line 53-57). On the other hand, Curcerzan disclosed “relevant verified statements from the current set of verified statements that are most relevant to the query” (Curcerzan: fig 1, 0022-0023,0032,0044).
As to Claim 6, the combination of Curtis, Curcerzan disclosed:
“for each of a plurality of initial queries” (Curtis :fig 2)
“obtaining, from the set of text segments, a respective subset of relevant text segments that are relevant to the initial query” (Curtis: col 10, line 1-21, fig 2, col 26, line 5-35);
“generating a respective prediction for the initial query of whether the initial query is by processing the initial query and the respective subset of relevant text segments using a first neural network” (Curtis: col 3, line 1-6, col 4, line 5-26, col 8, line 2-6, col 9, line 1-8);
“identifying respective predictions for the initial queries that indicate that the initial query” (Curtis: col 3, line 1-6, col 4, line 5-26);
“obtaining a respective confidence for each of the identified respective predictions” (Curtis: col 3, line 1-6, col 4, line 5-26, col 13, line 19-26); and
“initializing the current set of statements to include initial queries from the plurality of initial queries for which the respective confidence for the identified respective prediction meets a confidence threshold” (Curtis: col 13, line 19-26, line 44-58) . On the other hand, “valid, verified statements to include initial queries” (Cucerzan: fig 1, 0022-0023,0031-0032)
As to Claim 7, the combination of Curtis, Curcerzan disclosed:
for each of the plurality of initial queries (Curtis:fig 2) :
“obtaining, from the current set of statements, a respective subset of relevant statements that are relevant to the initial query” Curtis: fig 2, fig 3B, col 10, line 21-25, line 35-43. On the other hand, Cucerzan disclosed “valid, verified statements to include initial queries” (Cucerzan: fig 1, 0022-0023,0031-0032)
As to Claim 8, 10, the combination of Curtis, Curcerzan disclosed:
wherein obtaining, from a current set of statements, a subset of relevant statements that are relevant to the query comprises providing the query and the current set of statements as input to a statement retriever machine learning model that is configured to generate an output that identifies a subset of relevant statements from the current set of statements that are most relevant to the query, and wherein obtaining, from the current set of statements, a respective subset of relevant statements that are relevant to the initial query comprises providing the initial query and the current set of statements as input to the statement retriever machine learning model” (Curtis: fig 2, fig 3B, , col 4, line 31-39, col 7, line 44-54, col 8, line 56-61, col 10, line 21-25, line 35-43, col 11, line 53-57). On the other hand, Cucerzan disclosed “verified statements are relevant to the query” (Cucerzan: fig 1, 0022-0023,0031-0032)
As to Claim 9, the combination of Curtis, Curcerzan disclosed:
for each of a plurality of iterations: (Curtis:fig 2)
“increasing the confidence threshold; for each of the plurality of initial queries” (Curtis: col 13, line 10-26):
“generating a respective updated prediction for the initial query by processing the initial query, the respective subset of relevant text segments for the initial query, and the respective subset of relevant statements for the initial query using the query machine learning model” (Curtis : col 4, line 31-39, col 7, line 44-54, col 8, line 56-61,col 11, line 53-57);
“identifying respective updated predictions for the initial queries that indicate that the initial query” (Curtis: fig 2, fig 7, col 9, line 1-8);
“obtaining a respective confidence for each of the identified respective updated predictions” (Curtis: col 13, line 10-26;
“updating the current set of statements to include initial queries from the plurality of initial queries for which the respective confidence for the identified respective updated prediction meets the confidence threshold” (Curtis: col 13, line 19-26, line 44-58); and
for each of the plurality of initial queries (Curtis:fig 2)
“updating the respective subset of relevant statements for the initial query” (Curtis: fig 2, fig 7). On the other hand, Cucerzan disclosed “valid, verified statements to include initial queries” (Cucerzan: fig 1, 0022-0023,0031-0032)
As to Claim 11, the combination of Curtis, Curcerzan disclosed:
“for each of the plurality of initial queries: (Curtis:fig 2)
“generating a respective second updated prediction for the initial query by processing the initial query, the respective subset of relevant text segments for the initial query, and the respective subset of relevant statements for the initial query using the query machine learning model” (Curtis : col 4, line 31-39, col 7, line 44-54, col 8, line 56-61,col 11, line 53-57). On the other hand, Cucerzan disclosed “valid, relevant verified statements for the initial query” (Cucerzan: fig 1, 0022-0023,0031-0032)
As to Claim 12, the combination of Curtis, Curcerzan disclosed:
“updating the current set of statements to include initial queries from the plurality of initial queries for which the respective second updated prediction indicates that the initial query” (Curtis: col 13, line 19-26, line 44-58). On the other hand, Cucerzan disclosed “valid, verified statements to include initial queries” (Cucerzan: fig 1, 0022-0023,0031-0032)
As to Claim 13, the combination of Curtis, Curcerzan disclosed:
“ wherein at least a subset of the plurality of initial queries is obtained from a user” (Curtis: fig 2, fig 4A, fig 5A)
Claims 5,14, 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Curtis et al., (hereafter Curtis), US Patent No. 12,511,281 based on provisional application filed on Mar,2022, Cucerzan et al., (hereafter Cucerzan), US Pub. No. 2013/0268519 published Oct, 2013 in view of Raman et al., (hereafter Raman), US Pub. No. 2021/0374345 published Dec, 2021
Claim 5,19, Curtis disclosed:
“for each relevant text segment, process the query concatenated with the relevant text segment to generate a respective encoding for the relevant text segment” (Curtis: col 10, line 1-21, fig 2, col 26, line 5-35);
“for each relevant statement, process the query concatenated with the relevant verified statement to generate a respective for the relevant statement” (Curtis: fig 2, fig 4A, col 12, line 40-62, col 13, line 7-21)
“generate a input from the respective for the relevant text segments and the respective for the relevant statements” (Curtis: fig 2, col 26, line 24-40); and
“process the input using generate an output token representing the prediction of the query” (Curtis: col 3, line 1-6, col 4, line 5-26, col 9, line 1-8).
It is however, noted that Curtis does not disclose “relevant verified statements”. On the other hand, Curcerzan disclosed “relevant verified statements” (Curcerzan : fig 1, 0022-0023,0103)
It would have been obvious to a person of ordinary skill in the art at the time of filing the claimed invention verification engine that supports input statement particularly verification engine is trained to receive input statements of Curcerzan et al., into natural language queries into search query statements of Curtis et al., because that would have allowed users of Curtis to verify search queries particularly in the trained machine learning model thereby verification engine of Curcerzan include configuring to rewrite the input statement to get respective expected query output (Curcerzan: 0004-0005), as such both Curtis, Curcerzan specifically supports natural language query, training machine learning model (Curtis: Abstract, fig 5A-5B; Curcerzan: fig 2), and they both are from the same field of endeavor, thus improves overall quality and reliability of the system
It is however, noted that both Curtis, Curcerzan do not teach “generate respective encoding and decoder to generate output token”. On the other hand, Raman disclosed “generate respective encoding (Raman: Abstract, fig 1-2, 0040-0042, 0056 and decoder to generate output token” (Raman: 0043-0044, 0049)
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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 processing large-scale textual inputs using neural networks, particularly using machine learning task on respective input sequence of textual inputs of Raman et al., into users of Curtis, Curcerzan because all the prior arts are directed to processing natural language using machine learning (Curtis: fig 1, Abstract, col 11, line 53-57; Curcerzan: 0065, fig 5; and Raman: Abstract,0016-0017) and they are from same field of endeavor. Because all the prior arts teaches processing natural language using machine learning, training data, it would have been obvious to one skill ed in the art to substitute and/or modify one method for the other to identify, assign respective text processing ask(s) particularly processing semantic text matching tasks training plurality of encoder and/or decode, thereby allows to perform complex text sequences, while performing multi-task learning particularly different data types, generates respective text tokens using neural network (Raman: 0011-0013), thus improves overall quality and reliability of the system.
As to Claim 14, the combination of Curtis, Curcerzan, Raman disclosed:
“for each relevant text segment, process the initial query concatenated with the relevant text segment to generate a respective for the relevant text segment” (Curtis: fig 2, fig 4A, col 12, line 40-62, col 13, line 7-21)
“generate a input from the respective relevant text segments” (Curtis: fig 2, col 26, line 24-40); and
“process the input using to generate an output token representing the prediction of the initial query” (Curtis: col 3, line 1-6, col 4, line 5-26, col 9, line 1-8).
The prior art of Curcerzan disclosed “initial query is valid” (Curcerzan : fig 1, 0022-0023,0103 – using verification engine). On the other hand, Raman disclosed “generate respective encoding (Raman: Abstract, fig 1-2, 0040-0042, 0056 and process the decoder input using a first decoder to generate output token” (Raman: 0043-0044, 0049)
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Conclusion
The prior art made of record
a. US Patent. No. 12,511,281
b. US Pub. No. 2013/0268519
c. US Pub. No. 2021/0374345
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.
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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