DETAILED ACTION
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on April 24, 2026, has been entered.
In the response filed April 24, 2026, the Applicant amended claims 1 and 11; canceled claims 3, 7, 14, and 17; and added claims 23-26. Claims 1, 2, 5, 6, 8-12, 15, 16, and 18-26, are pending in the current application.
Notice of AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Arguments
Applicant’s arguments for claims 1, 2, 5, 6, 8-12, 15, 16, and 18-26, with respect to the 35 U.S.C. 101 rejection have been considered but are unpersuasive. Applicant argues that the claims are not directed to an abstract idea. Examiner respectfully disagrees. These steps, under broadest reasonable interpretation, describe or set-forth determining whether required parts/elements of design requirements of a product are present or absent to produce a compliance report of the product or “a process that evaluates a product requirement for a target aerospace component,” which amounts to concepts performed in the human mind (including an observation, evaluation, judgment, opinion). These limitations therefore fall within the “mental processes” subject matter grouping of abstract ideas.
Applicant argues that the claims recite specific technological operations which do not merely recite the identified abstract idea and therefore do not fall within a judicial exception. Examiner respectfully disagrees. The claim limitations identified by the Applicant such as “a trained machine learning model,” “a natural language processing model” “a graphical user interface (GUI),” (claims 1 and 11) and the requirement to execute the claims using the identified limitations is equivalent to adding the words “apply it” on a generic computer and/or mere instructions to implement the abstract idea on a generic computer. These limitations do not impose any meaningful limits on practicing the abstract idea, and therefore do/does not integrate the abstract idea into a practical application. See § MPEP 2106.05(f).
Viewing the additional limitations in combination also shows that they fail to ensure the claims amount to significantly more than the abstract idea. When considered as an ordered combination, the additional components of the claims add nothing that is not already present when considered separately, and thus simply append the abstract idea with words equivalent to “apply it” on a generic computer and/or mere instructions to implement the abstract idea on a generic computer. Applicant’s arguments remain unpersuasive.
Applicant argues that the claims integrate the judicial exception into a practical application as the trained models and predefined rubrics improve the accuracy and efficiency of compliance evaluation. Examiner respectfully disagrees. As discussed before, the claims as defined in the identified abstract idea describe concepts performed in the human mind. The execution of the defined abstract idea using “a computing system comprising: a processor coupled to a memory that stores instructions,” (claim 1); and “a trained machine learning model that has been trained using a training data set that includes input texts from historical product requirements and ground truth data indicating the requirement type for each input text;” “a natural language processing model” and “a graphical user interface (GUI),” (claims 1 and 11); “a category classification model that is configured to identify text entries with tags,” (claims 21 and 22), is equivalent to adding the words “apply it” on a generic computer and/or mere instructions to implement the abstract idea on a generic computer. The underlying process is one that amounts to a “mental processes” subject matter grouping of abstract ideas. A generically-recited general-purpose computer programmed to perform certain tasks/functions does not constitute a practical application in the field of aerospace engineering. Applicant’s arguments remain unpersuasive. The 35 U.S.C. 101 rejection is hereby maintained.
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, 2, 5, 6, 8-12, 15, 16, and 18-26, are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Step 1: Claims 1, 2, 5, 6, 8-10, 21, 24, and 25, are drawn to a device and claims 11, 12, 15, 16, 18-20, 22, 24, and 26, are drawn to a process, each of which is within the four statutory categories (e.g., a process, a machine). (Step 1: YES).
Step 2A – Prong One: In prong one of step 2A, the claims are analyzed to evaluate whether they recite a judicial exception.
Claim 1 (representative of claim 11) recites/describes the following steps:
“store input text of a product requirement for a target aerospace component;”
“identify a requirement type for the input text from among a plurality of candidate requirement types,”
“determine a plurality of required elements for the identified requirement type from among a plurality of candidate elements, using a predefined requirements rubric that determines, for each requirement type, a respective set of required elements applicable to the product requirement for the target aerospace component;”
“perform natural language processing on the input text… to thereby apply one or more tags from a predefined tagset to respective portions of the input text to generate tagged input text;”
“apply one or more predefined element identification rules to the tagged input text, to thereby identify a presence or absence of each of the plurality of required elements in the input text for the product requirement;”
“output an indication of the identified presence or absence of each of the plurality of the required elements in the product requirement and a score, wherein the indication indicates non-compliance of the product requirement for the target aerospace component with the predefined requirements rubric for the requirement type, and the score indicates a level of the presence or absence of each of the plurality of the required elements;” and
“generate, …, a report based on the indication and the score, the report indicating the presence or absence of each of the plurality of required elements and graphically indicating, using one or more visual indicators, a level of completeness of the product requirement with respect to the plurality of required elements, …wherein the score includes at least one of: a numerical value indicating the level of the presence or absence of each of the plurality of the required elements; a classification confidence value for a classification of the presence or absence of each of the plurality of the required elements; and a value indicating a level of ambiguity associated with the presence or absence of the required elements.”
These steps, under broadest reasonable interpretation, describe or set-forth determining whether required parts/elements of design requirements of a product are present or absent to produce a compliance report of the product or “a process that evaluates a product requirement for a target aerospace component,” which amounts to concepts performed in the human mind (including an observation, evaluation, judgment, opinion). These limitations therefore fall within the “mental processes” subject matter grouping of abstract ideas.
As such, the Examiner concludes that claim 1 recites an abstract idea (Step 2A – Prong One: YES).
Dependent claims 2 and 12 recite the same abstract idea as the independent claims because it recites the limitation “wherein the product requirement is selected from the group consisting of government rules, regulations, and contract requirements,” that further defines the processes of the abstract idea. Claims 2 and 12 are rejected due to being abstract and does not recite any additional elements/limitations.
Dependent claims 5 and 15 recite the same abstract idea as the independent claims because it recites the limitation “wherein the natural language processing further includes a keyword replacement and/or keyword identification,” that further defines the processes of the abstract idea. Claims 5 and 15 are rejected due to being abstract and does not recite any additional elements/limitations.
Dependent claims 6 and 16 recite the same abstract idea as the independent claims because it recites the limitation “wherein the keyword identification identifies whether the input text contains a predetermined keyword,” that further defines the processes of the abstract idea. Claims 6 and 16 are rejected due to being abstract and does not recite any additional elements/limitations.
Dependent claims 8 and 18 recite the same abstract idea as the independent claims because it recites the limitation “wherein the plurality of candidate requirement types are selected from the group consisting of a functional requirement, design requirement, environmental requirement, and suitability requirement,” that further defines the processes of the abstract idea. Claims 8 and 18 are rejected due to being abstract and does not recite any additional elements/limitations.
Dependent claims 9 and 19 recite the same abstract idea as the independent claims because it recites the limitation “wherein the plurality of required elements are selected from the group consisting of an agent element, function element, output element, performance element, timing element, and condition element,” that further defines the processes of the abstract idea. Claims 9 and 19 are rejected due to being abstract and does not recite any additional elements/limitations.
Dependent claims 10 and 20 recite the same abstract idea as the independent claims because it recites the limitation “wherein the one or more predefined element identification rules include one or more of an ordering rule, a singularity rule, and/or a keyword rule,” that further defines the processes of the abstract idea. Claims 10 and 20 are rejected due to being abstract and does not recite any additional elements/limitations.
Dependent claims 21 and 22 recite the additional limitation “a category classification model that is configured to identify text entries with tags,” which is addressed in step 2A (prong two) and step 2B below.
Dependent claims 23 and 24 recite the same abstract idea as the independent claims because it recites the limitation “wherein the report includes a pie chart indicating the level of completeness of the product requirement with respect to the plurality of required elements,” that further defines the processes of the abstract idea. Claims 23 and 24 are rejected due to being abstract and does not recite any additional elements/limitations.
Dependent claims 25 and 26 recite the same abstract idea as the independent claims because it recites the limitation “wherein the report includes a graph that indicates, for each of the plurality of required elements, a number or percentage of product requirements in which the required element is present and a number or percentage of product requirements in which the required element is absent due to non-compliance with the one or more predefined element identification rules,” that further defines the processes of the abstract idea. Claims 25 and 26 are rejected due to being abstract and does not recite any additional elements/limitations.
Step 2A – Prong Two:
The claims recite the additional elements/limitations of: “a computing system comprising: a processor coupled to a memory that stores instructions,” (claim 1); and “a trained machine learning model that has been trained using a training data set that includes input texts from historical product requirements and ground truth data indicating the requirement type for each input text;” “a natural language processing model” and “a graphical user interface (GUI),” (claims 1 and 11); “a category classification model that is configured to identify text entries with tags,” (claims 21 and 22).
The requirement to execute the claimed steps/functions using “a computing system comprising: a processor coupled to a memory that stores instructions,” (claim 1); and “a trained machine learning model that has been trained using a training data set that includes input texts from historical product requirements and ground truth data indicating the requirement type for each input text;” “a natural language processing model” and “a graphical user interface (GUI),” (claims 1 and 11); “a category classification model that is configured to identify text entries with tags,” (claims 21 and 22), is equivalent to adding the words “apply it” on a generic computer and/or mere instructions to implement the abstract idea on a generic computer. These limitations do not impose any meaningful limits on practicing the abstract idea, and therefore do/does not integrate the abstract idea into a practical application. See § MPEP 2106.05(f).
The claims also recite the additional elements/limitations of: “thereby providing an automated process that identifies missing information or errors in the product requirement and generates the report,” (claims 1 and 11).
The requirement to execute the claimed steps/functions “thereby providing an automated process that identifies missing information or errors in the product requirement and generates the report,” (claims 1 and 11), is equivalent to mere instructions to implement the abstract idea on a generic computer as it recites only the idea of a solution or outcome. These limitations do not impose any meaningful limits on practicing the abstract idea, and therefore do/does not integrate the abstract idea into a practical application. See MPEP 2106.05(f).
Remaining dependent claims 2, 5, 6, 8-10, 12, 15, 16, and 18-26, either recite the same additional elements as noted above or fail to recite any additional elements (in which case, note prong one analysis as set forth above – those claims are further part of the abstract idea as identified by the Examiner for each respective dependent claim).
The Examiner has therefore determined that the additional elements, or combination of additional elements, do not integrate the abstract idea into a practical application. Accordingly, the claims are directed to an abstract idea (Step 2A – Prong two: NO).
Step 2B:
As discussed above in “Step 2A – Prong 2,” the requirement to execute the claimed steps/functions using “a computing system comprising: a processor coupled to a memory that stores instructions,” (claim 1); and “a trained machine learning model that has been trained using a training data set that includes input texts from historical product requirements and ground truth data indicating the requirement type for each input text;” “a natural language processing model” and “a graphical user interface (GUI),” (claims 1 and 11); “a category classification model that is configured to identify text entries with tags,” (claims 21 and 22), is equivalent to adding the words “apply it” on a generic computer and/or mere instructions to implement the abstract idea on a generic computer. These limitations therefore do not qualify as “significantly more.” See MPEP § 2106.05(f).
As discussed above in “Step 2A – Prong 2,” the requirement to execute the claimed steps/functions “thereby providing an automated process that identifies missing information or errors in the product requirement and generates the report,” (claims 1 and 11), is equivalent to mere instructions to implement the abstract idea on a generic computer as it recites only the idea of a solution or outcome. These limitations do not impose any meaningful limits on practicing the abstract idea, and therefore do/does not integrate the abstract idea into a practical application. See MPEP 2106.05(f).
Viewing the additional limitations in combination also shows that they fail to ensure the claims amount to significantly more than the abstract idea. When considered as an ordered combination, the additional components of the claims add nothing that is not already present when considered separately, and thus simply append the abstract idea with words equivalent to “apply it” on a generic computer and/or mere instructions to implement the abstract idea on a generic computer.
Remaining dependent claims 2, 5, 6, 8-10, 12, 15, 16, and 18-26, either recite the same additional elements as noted above or fail to recite any additional elements (in which case, note prong one analysis as set forth above – those claims are further part of the abstract idea as identified by the Examiner for each respective dependent claim).
The Examiner has therefore determined that no additional element, or combination of additional claims elements is/are sufficient to ensure the claims amount to significantly more than the abstract idea identified above (Step 2B: NO).
Indication of Novel and Non-Obvious Subject Matter
Claims 1, 2, 5, 6, 8-12, 15, 16, and 18-26, recite novel and non-obvious subject matter. Each of the dependent claims recite novel and non-obvious subject matter by virtue of their dependency on independent claims 1 and 11.
As per claim 1 (representative of claim 11), the closest prior art of record taken either individually or in combination with other prior art of record fails to teach or suggest “identify a requirement type for the input text from among a plurality of candidate requirement types, using a trained machine learning model that has been trained using a training data set that includes input texts from historical product requirements and ground truth data indicating the requirement type for each input text; determine a plurality of required elements for the identified requirement type from among a plurality of candidate elements, using a predefined requirements rubric that determines, for each requirement type, a respective set of required elements applicable to the product requirement for the target aerospace component; perform natural language processing on the input text, using a natural language processing model, to thereby apply one or more tags from a predefined tagset to respective portions of the input text to generate tagged input text; apply one or more predefined element identification rules to the tagged input text, to thereby identify a presence or absence of each of the plurality of required elements in the input text for the product requirement; output an indication of the identified presence or absence of each of the plurality of the required elements in the product requirement and a score, wherein the indication indicates non-compliance of the product requirement for the target aerospace component with the predefined requirements rubric for the requirement type, and the score indicates a level of the presence or absence of each of the plurality of the required elements; and generate, via a graphical user interface (GUI), a report based on the indication and the score, the report indicating the presence or absence of each of the plurality of required elements and graphically indicating, using one or more visual indicators, a level of completeness of the product requirement with respect to the plurality of required elements, thereby providing an automated process that identifies missing information or errors in the product requirement and generates the report, wherein the score includes at least one of: a numerical value indicating the level of the presence or absence of each of the plurality of the required elements; a classification confidence value for a classification of the presence or absence of each of the plurality of the required elements; and a value indicating a level of ambiguity associated with the presence or absence of the required elements.” This combination of functions/features would not have been obvious to a PHOSITA in view of the prior art.
Prior Art of Record
The prior art made of record and not relied upon is considered pertinent to the applicant’s disclosure.
Litao et al. “Database Modeling Technology Research Based on Requirement Ontology” Journal of Physics: Conference Series. 2277 (2022) 012006 introduces the concept of ontology, through the requirement ontology model. The system requirements are formed into a unified modular unit, and each modular unit has a structured logical relationship. The structured and modularized requirement model will form a complete requirement management platform in the DOORS tool, which will realize the basis of civil aircraft requirement management and improve the capability and efficiency of civil aircraft product design.
Conclusion
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/Patrick Kim/Examiner, Art Unit 3629
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