Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendment
In response to the office action mailed on 02/26/2026, applicant filed an amendment on 05/26/2026, amending claims 1, 9, and 13. The pending claims are 1-20.
Response to Arguments
Applicant's filed arguments have been fully considered but they are not persuasive.
With regard to the claims’ rejection under 35 U.S.C. 101, applicant argues that the elements of the present claims do not comport with the Office's characterization of the claims as merely a "mental process." For example, "automatically identifying an access level of the user" and "generating the prompt based on a combination of the input, the data associated with the portion of the record, and the metadata associated with the portion of the record in a computer- readable instructions format" cannot practically be performed in the human mind.
The examiner notes the limitations of "automatically identifying an access level of the user" and "generating the prompt based on a combination of the input, the data associated with the portion of the record, and the metadata associated with the portion of the record in a computer- readable instructions format", as drafted by claims 1and 13, is a process that, under its broadest reasonable interpretation, covers performance of the limitations in the mind but for the recitation of generic computer components. That is, other than reciting “by a processor,” nothing in the claim element precludes the step from practically being performed in the mind. As to the automation argument, the examiner notes that automation of manual processes, such as using a generic computer to process an application and speeding up a process neither adds structure to claims language, nor shows an improvement in computer-functionality. Generating a prompt and providing it to a large language model is considered as a mere data gathering and/or output recited at a high level of generality, and thus is insignificant extra-solution activity. See MPEP 2106.05(g). The claimed components are recited at high level of generality. There is no details about how the claimed steps are performed and how the large language model operates. 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. Accordingly, the claim recites an abstract idea.
Applicant argues that the claimed steps of "automatically identifying an access level of the user," "identifying a portion of a record associated with the input based on the access level of the user," "identifying metadata associated with the portion of the record," "identifying data associated with the portion of the record," and "generating the prompt based on a combination of the input, the data associated with the portion of the record, and the metadata associated with the portion of the record in a computer-readable instructions format" integrate any purported judicial exception into a practical application of automatically and efficiently generating a prompt and are additional elements that amount to significantly more than the judicial exception because these additional elements recite, in ordered combination, a specific computer functionality that is not mere instructions to apply a judicial exception using generic components.
The examiner notes that claimed steps are conventional and well known as evidenced by the prior art of record. Automatically generating a prompt does not integrate the recited abstract idea into a practical application because the claim limitations do not impose any meaningful limits on practicing the abstract idea. Stated differently, the claims do not (1) improve the functioning of a computer or other technology, (2) are not applied with any particular machine (except for generic computer components), (3) do not effect a transformation of a particular article to a different state, and ( 4) are not applied in any meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim, as a whole, is no more than a drafting effort designed to monopolize the exception. In order to show involvement of a computer assists in improving the technology, the claims must recite the details regarding how a computer aids the method, the extent to which the computer aids the method, or the significance of a computer to the performance of the method. Accordingly, the claims are directed to an abstract idea.
With regard to prior art, applicant, argues that the prior art does not teach “receiving an input from a user, wherein the input is associated with a record, the record being interrelated and linked to at least one data field in at least one additional record”.
The examiner notes that Gassner teaches receiving an input from a user ([0060]- [0067], receiving, from a user, a request for accessing a document), wherein the input is associated with a record (the request is associated with a particular record, i.e. a user and/or a document to be accessed), the record being interrelated and linked to at least one data field in at least one additional record (the record which is the user and/or document is interrelated and linked to at least one data field, i.e. the user is interrelated and linked to a plurality of groups that the user is assigned to; and the requested document is also interrelated and linked to at least one data field on an object record ([0067]).
As per the rest of the claims, and combinations of prior art reference, applicant has no further arguments beside the ones mentioned above. Therefore, all the combinations of prior art reference mentioned above are valid, and all other claims are rejected for the same reasons as set above.
Claim Rejections - 35 USC § 101
4. 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 non-statutory subject matter. 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: Is the claimed invention to a process, machine, manufacture or composition of matter?
The claimed invention, at independent claims 1 and 13, is directed to a method (process) and computer readable medium (manufacture) for receiving an input from a user; identifying an access level of the user; identifying a portion of a record associated with the input based on the access level of the user; identifying data associated with the portion of the record; identifying metadata associated with the portion of the record; generating the prompt based on a combination of the input, the data associated with the portion of the record, and the metadata associated with the portion of the record in a natural language format; and providing the prompt to the large language model.
Step 2A, prong 1: Does the claim recite an abstract idea, law or nature, or natural phenomenon?
Under the 35 U.S.C. 101 new guidelines, the broadest reasonable interpretation of the claims, the claimed steps fall within the “Mental Processes” grouping of abstract ideas because they cover concepts performed in the human mind, including observation, evaluation, judgment, and opinion. See MPEP 2106.04(a)(2), subsection III.
The steps of receiving an input from a user; identifying an access level of the user; identifying a portion of a record associated with the input; identifying data associated with the portion of the record; identifying metadata associated with the portion of the record; generating the prompt based on a combination of the input, the data associated with the portion of the record, and the metadata associated with the portion of the record in a natural language format; and providing the prompt to the large language model, encompass mental processes practically performed in the human mind using observation, evaluation, judgment, and opinion. For example, a person can receive input from a user; identify information related to the user and content of the input such as access level of the user, a record associated with the input, data associated with a portion of the record; and generate a prompt based on the identified information without using a machine. See MPEP 2106.04(a)(2), subsection III.
The step of providing the prompt to a large language model does not provide any details about how the large language model operates. The limitation is a mere data gathering and/or output recited at a high level of generality, and thus is insignificant extra-solution activity. See MPEP 2106.05(g). Therefore, the claimed steps fall within the mental process grouping of abstract ideas.
Step 2A, prong 2: Does the claim recite additional elements that integrate the judicial exception into a practical application?
The claim recites the additional elements of “instructions executed by at least one processor” and “and providing a prompt to a large language model” are mere data gathering and manipulating recited at high level of generality, and thus are insignificant extra-solution activity The processor is recited at a high level of generality, and it amounts to no more than mere instructions to apply the exception using a generic computer. See MPEP 2106.05(f). The mere nominal recitation of a generic network appliance does not take the claims limitations out of the mental processes grouping. Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application, and the claims are directed to the judicial exception.
Step 2B: Does the claim recite additional elements that amount to significantly more than the abstract idea?
As to whether the claims as a whole amount to significantly more than the recited exception, i.e., whether any additional element, or combination of additional elements, adds an inventive concept to the claim (Step 2B), as explained above in Step 2A, Prong 2, the use of “processor” is at high level of generality, and even when considered in combination, these additional elements represent mere instructions to apply an exception and insignificant extra-solution activity, and therefore do not provide an inventive concept. Accordingly, the claims are ineligible.
Dependent claims 2-12 and 14-20 further refer and describe the process of identifying data and corresponding relationship, generating the prompt, providing the prompt as in claims 2, 4-5, 8-9, 14-15, 17-18, 20, which encompasses a mental process that is practically performed in the human mind, as explained above in Step 2A, Prong 1. Claims 3, 6-7 and 10-11, 16, 19 further describe the claimed record, input, generated prompt, and metadata. Claim 12 recites receiving answer data from the large language model; and transmitting the answer data to the user, which is a mere data gathering and/or output recited at a high level of generality, and thus is insignificant extra-solution activity.
Accordingly, claims 1-20 are directed to an abstract idea, and are not patent eligible.
Claim Rejections - 35 USC § 103
5. 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 (i.e., changing from AIA to pre-AIA ) 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.
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.
Claims 1-8, 10-17, and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Gassner (US 20190238551) in view of Eberlein (US 2025/0156574).
As per claim 1, Gassner teaches a non-transitory computer readable medium including instructions that, when executed by at least one processor, cause the at least one processor to perform operations ([0022]) comprising:
receiving an input from a user ([0060]- [0067], receiving, from a user, a request for accessing a document), wherein the input is associated with a record (the request is associated with a particular record, i.e. a user and/or a document to be accessed), the record being interrelated and linked to at least one data field in at least one additional record (the record which is the user and/or document is interrelated and linked to at least one data field, i.e. the user is interrelated and linked to a plurality of groups that the user is assigned to; and the requested document is also interrelated and linked to at least one data field on an object record ([0067]);
identifying an access level of the user ([0028], wherein a user's access permissions are defined based on his/her responsibilities and/or skillsets, and may include role, product, country, document type and other attributes. [0061] – [0062], determining by the access management module if any of the groups that the user is assigned to is stamped to the document. See also, [0085], wherein said, the first user, a study manager, has the Read and Edit permissions on the object and all its fields);
identifying a portion of a record associated with the input based on the access level of the user ([0065], wherein the content management system identifies which row/record level is to be accessed by the user);
identifying data associated with the portion of the record ([0067], identifying data within a specific row or a specific field, data which a user can view or edit); and
identifying metadata associated with the portion of the record ([0067], for state/role field level security, data about a certain state of the lifecycle of the document is determined to provide access to the user).
Gassner may not explicitly disclose generating the prompt based on a combination of the input, the data associated with the portion of the record, and the metadata associated with the portion of the record in a computer-readable instruction format; and providing the prompt to the large language model. Eberlein in the same field of endeavor teaches a system data access control for large language model services (Abstract), and generating the prompt based on a combination of the input, the data associated with the portion of the record, and the metadata associated with the portion of the record in a computer-readable instruction format; and providing the prompt to the large language model ([0052]- [0057], wherein a prompt generator creates a content for prompts and passes the created prompts to a LLM to retrieve the accessible information). As to the computer-readable instruction format, Eberlein teaches using structured format as in paragraph [0028], wherein a client application that uses parameters, metadata, and other API and event dependency information received at launch to access a particular LLM 108 from the server system. So, if Eberlein teaches providing instructions to the LLM in a structured machine- processable format, a person of ordinary skill in the art would have understood such structured prompts to be in a computer-readable instruction format because they are encoded in a syntax that the receiving computer system parses and processes. Therefore, it would have been obvious at the time the application was filed to use the above features of Eberlein with the system of Gassner, in order to improve accuracy and relevance of output results.
As per claim 2, identifying at least one additional record related to the record; identifying, based on the access level of the user, data associated with a portion of the at least one additional record accessible to the user; identifying a relationship between the record and the at least one additional record. Gassner teaches a content management system that has several layers of access controls, which may include a layer of access control at the object level, a layer of access control at the row/record level and a layer of access control at the field level ([0065]). At each level, an additional record is identified and processed, and additional associated data and corresponding relationship is determined to control access at every level. Therefore, identifying at least one additional record related to the record; identifying, based on the access level of the user, data associated with a portion of the at least one additional record accessible to the user; identifying a relationship between the record and the at least one additional record is necessarily disclosed by the teaching of Gassner. Furthermore, Eberlein in the same field of endeavor teaches a system data access control for large language model services (Abstract), wherein application logic 404 generates a query for the application object instance using the required information to generate, using the prompt generator 422, the prompt (e.g., additional relevant attributes about employee “John Doe”). More, generating the prompt based on a combination of the input, the data associated with the portion of the record, and the metadata associated with the portion of the record in a natural language format; and providing the prompt to the large language model ([0052]- [0057], wherein a prompt generator creates a content for prompts and passes the created prompts to a LLM to retrieve the accessible information). Therefore, it would have been obvious at the time the application was filed to use the above features of Eberlein with the system of Gassner, in order to improve accuracy and relevance of output results.
As per claim 3, Gassner teaches wherein the record includes a plurality of identifiers, and wherein the plurality of identifiers identify a plurality of additional records ([0033], Documents attributes, documents IDs, products).
As per claim 4, wherein the operations further comprise identifying metadata associated with at least one additional record from the plurality of additional records accessible to the user based on the access level of the user, wherein the metadata comprises a relationship between the record and the at least one additional record. Gassner teaches a content management system that has several layers of access controls, which may include a layer of access control at the object level, a layer of access control at the row/record level and a layer of access control at the field level ([0065]). At each level, an additional record is identified and processed, and additional associated metadata (as in paragraph [0067], for state/role field level security, data about a certain state of the lifecycle of the document (metadata) is determined to provide access to the user), and corresponding relationship is determined to control access at every level. Therefore, identifying the claimed metadata is necessarily disclosed within the process of controlling access to documents, as set by Gassner.
As per claim 5, Gassner teaches identifying at least two of: the input, the metadata associated with the at least one additional record, the data associated with the portion of the record, and the metadata associated with the portion of the record, as evidenced by paragraphs [0065]- [0067]. Gassner may not explicitly disclose generating the prompt based on a combination of at least two of: the input, the metadata associated with the at least one additional record, the data associated with the portion of the record, and the metadata associated with the portion of the record. Eberlein in the same field of endeavor teaches a system data access control for large language model services (Abstract), and generating the prompt based on a combination of the input, the data associated with the portion of the record, and the metadata associated with the portion of the record in a natural language format; and providing the prompt to the large language model ([0052]- [0057], wherein a prompt generator creates a content for prompts and passes the created prompts to a LLM to retrieve the accessible information). Therefore, it would have been obvious at the time the application was filed to use the above features of Eberlein with the system of Gassner, in order to improve accuracy and relevance of output results.
As per claim 6, Gassner teaches wherein the input comprises at least one of: a request to summarize the record, a request about features of the record, or a request to generate an output based on the record ([0018], wherein said, a server may simultaneously process requests from a plurality of customers, and the content storage system 111 may store content for a plurality of customers; and [0065], wherein the request may be about read, edit, or delete of the record).
As per claim 7, Gassner teaches wherein the input comprises at least one of: a pre-generated question or a user-generated question ([0060], a user request for accessing a document).
As per claim 8, Gassner may not explicitly disclose wherein providing the prompt to the large language model comprises transmitting the prompt through a proxy. Eberlein in the same field of endeavor teaches a proxy server ([0026]) that applies a machine learning model to process, clean, and create a normalized variant of the question (prompt) that can be sent to the LLM ([0041], [0046]). Therefore, it would have been obvious at the time the application was filed to use the above features of Eberlein with the system of Gassner, in order to improve accuracy and relevance of output results.
As per claim 10, Gassner may not explicitly disclose wherein the prompt further comprises instructions for the large language model to interpret the record and the metadata. Eberlein in the same field of endeavor teaches providing the LLM with information needed for interpreting the record and metadata ([0057]). Therefore, it would have been obvious at the time the application was filed to use the above feature of Eberlein with the system of Gassner, in order to improve accuracy and relevance of output results.
As per claim 11, Gassner teaches wherein the metadata associated with the record comprises at least one of: a field-level display name, a field-level description, a record type display name, and a record type description ([0067]).
As per claim 12, may not explicitly disclose receiving answer data from the large language model; and transmitting the answer data to the user. Eberlein in the same field of endeavor teaches receiving answer data from the large language model; and transmitting the answer data to the user ([0047], wherein the LLM can compute the response and can send the response to the application logic 404, which derives an action to be executed or response to be sent to the user device, which had submitted the question). Therefore, it would have been obvious at the time the application was filed to use the above feature of Eberlein with the system of Gassner, in order to provide relevant answers and improve customer service operations.
As per claims 13, 17, 19, and 20, method claims 13, 17, 19, 20 and computer readable medium claims 1, 2, 4, 8, 11 are related as method and apparatus of using same. Accordingly claims 13, 17, 19, 20 are similarly rejected under the same rationale as applied above with respect to computer readable medium claims 1, 2, 4, 8, 11.
As per claims 14 and 15, Gassner may not explicitly disclose receiving, from the large language model, answer data identifying at least one additional record related to the prompt; identifying data associated with a portion of the at least one additional record accessible to the user based on the access level of the user; generating a second prompt, wherein the second prompt includes the data associated with the portion of the at least one additional record; and providing the second prompt to the large language model, wherein the second prompt further comprises metadata related to a context or a nature of a relationship between the record and the at least one additional record. Eberlein in the same field of endeavor teaches receiving, from the large language model, answer data identifying at least one additional record related to the prompt ([0047]). Furthermore, Eberlein teaches receiving a feedback based on the displayed response to the initial question is automatically requested. The feedback can indicate an approval level of the response and can be used for further training the machine learning model. Therefore, based on the teaching of it would have been obvious at the time the application was filed to use the above feature of Eberlein with the system of Gassner, in order to identify data associated with a portion of the at least one additional record accessible to the user based on the access level of the user; generate a second prompt, wherein the second prompt includes the data associated with the portion of the at least one additional record; and providing the second prompt to the large language model, wherein the second prompt further comprises metadata related to a context or a nature of a relationship between the record and the at least one additional record. This would improve accuracy and relevance of output results.
As per claim 16, Gassner teaches wherein the record comprises at least one of: a use case record, a customer record, or a support case record ([0018]).
Claims 9 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Gassner (US 20190238551) in view of Eberlein (US 2025/0156574), and further in view of Lee (CN 101340278).
As per claims 9 and 18, Gassner in view of Eberlein may not explicitly disclose wherein the proxy provides authentication to the large language model. Lee in the same field of endeavor teaches a proxy providing authentication to a large language model ([0075]). Therefore, it would have been obvious at the time the application was filed to use Lee’s feature of authenticating a large language model by a proxy, with the system of Gassner in view of Eberlein, in order to enhance security and optimize processing costs.
Conclusion
6. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. See PTO-892.
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 ABDELALI SERROU whose telephone number is (571)272-7638. The examiner can normally be reached M-F 9 Am - 5 PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Pierre-Louis Desir can be reached at 571-272-7799. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ABDELALI SERROU/Primary Examiner, Art Unit 2659
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