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 .
Claims 1, 3-10, 12-15, 17-20 are pending for examination. Claims 1, 10, and 15 are independent.
Response to Amendment
This office action is responsive to the amendments filed on 08/24/2026. As directed by the amendments, Claims 1, 10, and 15 are amended. Claims 2, 11, and 16 are cancelled.
Response to Arguments
The following is the Examiner’s response to the Applicant’s arguments and remarks filed on 08/24/2026.
Information Disclosure Statement (IDS)
Examiner’s response: Legible copies of the non-patent literature #4 (Schmid et al.) identified in the IDS filed 09/28/2023, and non-patent literature #3 (office action mailed 08/05/2025) identified in the IDS filed 08/11/2025 have been filed on 08/13/2026 alongside an IDS. The IDS has been fully considered.
Drawings
Examiner’s response: Applicant’s arguments and amendments, see page 9 of Remarks and Drawings – Replacement Sheets, filed 08/24/2026, with respect to Objection to Drawings have been fully considered and are persuasive. The Objection to Drawings has been withdrawn.
Specification
Examiner’s response: Applicant’s arguments and amendments, see page 10 of Remarks and Amendments to the Specification, filed 08/24/2026, with respect to Objection to Specification have been fully considered and are persuasive. The Objection to Specification has been withdrawn.
35 U.S.C. § 101
Applicant argues: (2A Prong 1, Pages 11-12) The claims, as amended, cannot practically be performed in the human mind. The amended claims do not merely amount to observations, evaluations, judgements, opinions, or any other example of a mental process identified in MPEP 2106.04(a)(2)(III) and provide computer-implemented conformance analysis using an LLM, a specific technological application that the human mind is not equipped to perform.
(2A Prong 2, Pages 12-14) The claims improve a process mining system / functioning of a computer or other technology. Specifically, the claims are integrated into the practical application of an improved process mining system for determining corrective action that transforms non-conforming execution of a process into conforming execution. Applicant Remarks Page 13 describe a specific technical problem and remark that “this technical improvement is reflected in the claims.
(2B, Pages 14-15) The claims are not WURC, the combination of features provides for an inventive concept that amounts to significantly more than the alleged abstract idea.
Examiner’s response: Applicant’s arguments have been fully considered but they are not persuasive. Regarding Step 2A Prong 1, the claims as amended broadly describe generating a description of 1) nonconformance of the instance of execution to the process model and 2) one or more modifications of the instance of execution of the process that result in conformance of the instance of execution to the process model which can practically be performed in the human mind with the aid of pencil and paper (i.e. evaluation). Applicant specification [0080] discloses that Fig. 7 exemplifies cases where a description of non-conformance and recommended modifications of the instance of execution that result in conformance is provided. A person may explain with pencil and paper why an instance of execution does not match the expected output of a process mode, and what modifications may be performed to the instance of execution in order to result in conformance. The large language model used to perform the functions described in the amended claims is understood to be a generic computer element merely describing using a computer as a tool to perform this mental process or abstract idea.
Regarding Step 2A Prong 2, the claims as amended broadly describe receiving one or more prompts and outputting the description of the non-conformance and the one or more modifications of the instance of execution of the process, which remain understood as insignificant extra-solution activities exemplary of mere data gathering and presenting offers respectively (MPEP 2106.05(g and d)). On Page 13 of Remarks, Applicant has recited the technical problem described in the Specification and a statement that the technical improvement is reflected in the claims with no further remark. MPEP 2106.04(d)(1) states the specification must describe the invention such that the improvement would be apparent to one of ordinary skill in the art. Conversely, if the specification explicitly sets forth an improvement but in a conclusory manner (i.e., a bare assertion of an improvement without the detail necessary to be apparent to a person of ordinary skill in the art), the examiner should not determine the claim improves technology. Second, if the specification sets forth an improvement in technology, the claim must be evaluated to ensure that the claim itself reflects the disclosed improvement.
Regarding Step 2B, the claims as amended broadly describe receiving one or more prompts and outputting the description of the non-conformance and the one or more modifications of the instance of execution of the process, which remain understood as well-understood, routine, conventional activities exemplary of receiving data and presenting offers respectively (MPEP 2106.05(g and d)). Page 14 Para. 4 of Applicant’s Remarks mentions “the cited reference” in an argument for reconsidering the rejection, which bears no weight when examining under 35 U.S.C. §101, as there is no requirement for evidence to support a finding that the exception is not integrated into a practical application or that the additional elements do not amount to significantly more than the exception unless the examiner asserts that the additional limitations are well-understood, routine, conventional activities – see MPEP 2106.07(a)(III). With regard to the rejections presented under Step 2B, Examiner has only previously referred to recognized elements in MPEP 2106.05(d)(II) to exemplify additional claim elements that are well-understood, routine, conventional activities.
Applicant’s arguments with respect to Examiner’s rejections under 35 U.S.C. §101 have been considered but are not persuasive for the reasons aforementioned. Examiner maintains the rejection of the amended claims under 35 U.S.C. §101 as described below.
35 U.S.C. § 102
Applicant argues: “The first paragraph of Listing 15 of Berti explicitly states as much: "From the process variants and the frequency and performance statistics provided, there are a few keys steps that could be causing performance issues in the process." However, merely identifying steps that could be causing performance issues in Listing 15 of Berti does not teach or suggest "non-conformance of the instance of execution to the process model" as recited in claim 1. The root cause analysis in Listing 15 of Berti does not determine whether an instance of execution of a process conforms to a process” and
“Further, the root cause analysis in Listing 15 of Berti does not "generat[e] a description of one or more modifications of the instance of execution of the process that result in conformance of the instance of execution of the process to the process model" as recited in amended claim 1. As noted above, the root cause analysis in Listing 15 of Berti merely identifies steps of a process that could be causing performance issues and does not generate a description of modifications of the instance of execution of the process. Listing 15 of Berti is silent with regards to "conformance of the instance of execution of the process to the process model.”.
Examiner’s response: Applicant's arguments fail to comply with 37 CFR 1.111(b) because they amount to a general allegation that the claims define a patentable invention without specifically pointing out how the language of the claims patentably distinguishes them from the references.
Applicant’s claims are broad and do not specifically provide any details nor specific steps or function that disclose a description of non-conformance and/or one or more modifications of the execution of the process model that would result in conformance. In accordance with broadest reasonable interpretation, the cited reference Berti teaches as such:
First, the “key steps that could be causing performance issues in the process” as described in Listing 15 are interpreted as descriptions of nonconformance. Problematic steps such as “Missing Approval” in Listing 15 teaches an approval step within an ordered step-list that, when missing, demonstrates a non-conformance of the process instance to the process model that is described as an approval that is missing.
Second, Listing 15 does additionally provide a generated description of the one or more modifications of the instance of execution of the process that result in conformation to the process model, namely in the last section of Listing 15: “Solutions to these issues might include streamlining the approval process, providing better training or resources to reduce the number of rejections, or implementing a more efficient system for handling re-submissions.” To directly address the aforementioned example of “missing approval” in Listing 15, the citation also discloses “Approval by PRE_APPROVER, BUDGET OWNER or SUPERVISOR” that, when addressed, may be regarded as a step or modification to the process instance that addresses the non-conformance of the “missing approval” step and results in conformation of the instance of execution of the process to the process model.
Applicant’s arguments with respect to Claims anticipated by or made obvious in view of Berti have been considered but are not persuasive for the reasons aforementioned. Examiner maintains the rejection of the amended claims under 35 U.S.C. §102 and 35 U.S.C. §103 as described below.
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, 3-10, 12-15, and 17-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1: The claim is a process, machine, manufacture, or composition of matter.
In the instant application, Claims 1 and 3-9 are directed to a process, Claims 10 and 12-14 are directed to a machine, and Claims 15 and 17-20 are directed to a machine. Thus, each of the claims are directed to one of the four statutory categories (i.e. process, machine, manufacture, or composition of matter).
With respect to Claim 1:
2A Prong 1: The claim recites an abstract idea, law of nature, or natural phenomenon.
A computer-implemented method comprising: generating, (This step for generating a description of non-conformance and of one or more modifications of the instance of execution is practically performable in the human mind and is understood to be a recitation of a mental process with the aid of pen and paper (i.e. evaluation).)
2A Prong 2: The judicial exception is not integrated into a practical application.
A computer-implemented method comprising: receiving one or more prompts defining 1) instructions, 2) a textual description of a process model of a process, and 3) an instance of execution of the process; (Receiving is understood as insignificant extra-solution activity, being exemplary of mere data gathering –- see MPEP 2106.05(g).)
using a large language model (This step is reciting a judicial exception with the words “apply it” (or an equivalent), or merely invoking computers or machinery as a tool to perform the abstract idea (i.e. execution) – see MPEP 2106.05(f)(2).)
outputting the description of the non-conformance of the instance of execution to the process model and the one or more modifications of the instance of execution of the process. (Outputting is understood as a post-solution activity, being exemplary of presenting offers –- see MPEP 2106.05(g).)
The additional elements as disclosed above alone or in combination do not integrate the judicial exception into practical application as they are insignificant extra-solution activities in combination with generic implementation of a model as a tool to perform the abstract idea above.
2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
A computer-implemented method comprising: receiving one or more prompts defining 1) instructions, 2) a textual description of a process model of a process, and 3) an instance of execution of the process; (Receiving information is understood as a well-understood, routine, and conventional function, exemplary of receiving or transmitting data over a network –- see MPEP 2106.05(d)(II)(i).)
using a large language model (This step is reciting a judicial exception with the words “apply it” (or an equivalent), or merely invoking computers or machinery as a tool to perform the abstract idea (i.e. execution) – see MPEP 2106.05(f).)
outputting the description of the non-conformance of the instance of execution to the process model and the one or more modifications of the instance of execution of the process. (Outputting information is understood as a well-understood, routine, and conventional function, exemplary of presenting offers and gathering statistics –- see MPEP 2106.05(d)(II)(iv).)
The additional elements as disclosed above alone or in combination do not recite significantly more than a judicial exception as they are well-understood, routine, conventional activities previously known to the industry in combination with generic implementation of a model as a tool to perform the disclosed abstract idea above.
With respect to Claim 10:
see the rejection of Claim 1 above; the same rationale is applied.
2A Prong 2 & 2B: The claim recites another element “A system comprising: a memory storing computer program instructions; and at least one processor configured to execute the computer program instructions, the computer program instructions configured to cause the at least one processor to perform operations of:” (The memory and at least one processor are understood as mere instructions to apply the exception using a generic computer component –- see MPEP 2106.05(f).)
With respect to Claim 15:
see the rejection of Claim 1 above; the same rationale is applied.
2A Prong 2 & 2B: The claim recites another element “A non-transitory computer-readable medium storing computer program instructions, the computer program instructions, when executed on at least one processor, cause the at least one processor to perform operations comprising:” (The non-transitory computer-readable medium and at least one processor are understood as mere instructions to apply the exception using a generic computer component –- see MPEP 2106.05(f).)
With respect to Claims 3 and 12:
2A Prong 1: The claim recites an abstract idea, law of nature, or natural phenomenon.
The computer-implemented method of claim 1 and the system of claim 10 respectively, wherein the instructions comprise instructions for assigning a name to the process, the method further comprising: generating the name for the process . (This step for generating the name for the process is practically performable in the human mind and is understood to be a recitation of a mental process with the aid of pen and paper (i.e. judgement).)
2A Prong 2 & 2B:
using a large language model (This step is reciting a judicial exception with the words “apply it” (or an equivalent), or merely invoking computers or machinery as a tool to perform the abstract idea (i.e. execution) -- see MPEP 2106.05(f).)
With respect to Claims 4 and 13:
2A Prong 1: The claim recites an abstract idea, law of nature, or natural phenomenon.
The computer-implemented method of claim 1 and the system of claim 10 respectively, wherein the instructions comprise instructions for assigning a name to the instance of execution, the method further comprising: generating the name for the instance of execution (This step for generating the name for the instance of execution is practically performable in the human mind and is understood to be a recitation of a mental process with the aid of pen and paper (i.e. judgement).)
2A Prong 2 & 2B:
using a large language model (This step is reciting a judicial exception with the words “apply it” (or an equivalent), or merely invoking computers or machinery as a tool to perform the abstract idea (i.e. execution) – see MPEP 2106.05(f).)
With respect to Claims 5 and 14:
2A Prong 1: The claim recites an abstract idea, law of nature, or natural phenomenon.
The computer-implemented method of claim 1 and the system of claim 10 respectively, wherein the instructions comprise instructions for identifying and generating recommendations for fixing issues with names of activities of the process, the method further comprising: identifying the issues with the names of the activities of the process (This step for identifying issues with activity names is practically performable in the human mind and is understood to be a recitation of a mental process with the aid of pen and paper (i.e. evaluation).)
generating the recommendations for fixing the issues with the activities of the process (This step for generating recommendations for fixing issues with the activities of the process is practically performable in the human mind and is understood to be a recitation of a mental process with the aid of pen and paper (i.e. judgement).)
2A Prong 2 & 2B:
using a large language model (This step is reciting a judicial exception with the words “apply it” (or an equivalent), or merely invoking computers or machinery as a tool to perform the abstract idea (i.e. execution) – see MPEP 2106.05(f).)
With respect to Claims 6 and 17:
2A Prong 1: The claim recites an abstract idea, law of nature, or natural phenomenon.
The computer-implemented method of claim 1 and the non-transitory computer-readable medium of claim 15 respectively, wherein the instructions comprise instructions for generating recommendations for improving the process, the method further comprising: generating the recommendations for improving the process (This step for generating recommendations for improving the process is practically performable in the human mind and is understood to be a recitation of a mental process with the aid of pen and paper (i.e. judgement).)
2A Prong 2 & 2B:
using a large language model (This step is reciting a judicial exception with the words “apply it” (or an equivalent), or merely invoking computers or machinery as a tool to perform the abstract idea (i.e. execution) – see MPEP 2106.05(f).)
With respect to Claims 7 and 18:
2A Prong 1: The claim does not recite any Abstract idea.
2A Prong 2 & 2B:
The computer-implemented method of claim 1 and the non-transitory computer-readable medium of claim 15 respectively, wherein the instance of execution of the process is defined as a sequence of activities of the process. (The specification of the sequence of activities of the process is understood to be a field of use limitation. The limitation further specifies the instance of execution of the process – see MPEP 2106.05(h).)
With respect to Claims 8 and 19:
2A Prong 1: The claim does not recite any Abstract idea.
2A Prong 2 & 2B:
The computer-implemented method of claim 1 and the non-transitory computer-readable medium of claim 15 respectively, wherein the instance of execution is identified as being non-conforming to the process model using a process aligner. (This step is reciting a judicial exception with the words “apply it” (or an equivalent), or merely invoking computers or machinery as a tool to perform the abstract idea (i.e. identification) – see MPEP 2106.05(f).)
With respect to Claims 9 and 20:
2A Prong 1: The claim does not recite any Abstract idea.
2A Prong 2 & 2B:
The computer-implemented method of claim 1 and the non-transitory computer-readable medium of claim 15 respectively, wherein the process is an RPA (robotic process automation) workflow executed by one or more RPA robots. (This step is reciting a judicial exception with the words “apply it” (or an equivalent), or merely invoking computers or machinery as a tool to perform the abstract idea (i.e. execution) – see MPEP 2106.05(f).)
Claim Rejections - 35 USC § 102
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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1, 5-7, 10, 14-15, and 17-18 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Berti and Qafari ("Leveraging Large Language Models (LLMs) for Process Mining (Technical Report)"), hereinafter "Berti".
With respect to Claim 1:
Berti teaches: A computer-implemented method ([Page 24 §3 ¶1] describes tools such as Python (i.e. computer implemented.).) comprising:
receiving one or more prompts ([Page 22 §2.2.2 ¶1] discloses a “series of distinct prompts” used to guide the LLM. [Page 22 §2.2.1 ¶1] recites “This strategy involves formulating a prompt which combines a textual abstraction of a process mining artifact with a direct question related to it.”.) defining
1) instructions ([Page 22 §2.2.1 ¶1] discloses exemplary question “What are the bottlenecks of the process?”, which would correspond to an instruction. Applicant’s specification [0072] states that “instructions may include, for example, … questions.”.)
2) a textual description of a process model of a process ([Page 11 §2.1.1] describes textual abstractions of process models digestible by LLM.), and
3) an instance of execution of the process ([Page 2 §1.1 ¶1; Page 17 §2.1.2; Page 31 Table 11] describes textual abstractions of event logs.);
generating, using a large language model based on the textual description of the process model and the instructions, a description of non-conformance of the instance of execution to the process model and of one or more modifications of the instance of execution of the process that result in conformance of the instance of execution of the process to the process model; and ([Page 31 Table 11; Pages 34-35 Listings 15-16] wherein Listings 15 and 16 show a generated description of non-conformance, Listing 15 discloses that the description is based on a textual description of the process "From the process variants and the frequency and performance statistics provided," Listings 15 and 16 additionally illustrate recommended modifications of the instance of execution to the process: “Solutions to these issues might include” [Listing 15], “To address these performance issues, the company could consider the following” [Listing 16]. Table 11 provides Questions TQ1 - TQ12 alongside Textual Abstraction Used and the descriptions generated from select large language models.); and
outputting the description of the non-conformance of the instance of execution to the process model and the one or more modifications of the instance of execution to the process. ([Pages 34-35 Listings 15-16] are exemplary illustrations of LLM output of descriptions of non-conformance such as “Missing Approval” of Listing 15 or the root causes listed in Listing 16. These listings additionally illustrate recommended modifications of the instance of execution to the process: “Solutions to these issues might include” [Listing 15], “To address these performance issues, the company could consider the following” [Listing 16].)
With respect to Claim 10:
Berti teaches a system comprising: a memory storing computer program instructions ([Page 24 §3] describes tool support such as Python which implies the use of memory.); and
at least one processor configured to execute the computer program instructions, the computer program instructions configured to cause the at least one processor to perform operations of: ([Page 24 §3] describes tool support such as Python which implies the use of processors/computers.)
Claim 10 is a device claim that corresponds to Claim 1 and the remaining limitations are rejected for at least the same reasons therein.
With respect to Claim 15:
Berti teaches: A non-transitory computer-readable medium storing computer program instructions, the computer program instructions, when executed on at least one processor, cause the at least one processor to perform operations comprising: ([Page 24 §3] describes tool support such as Python which implies the use of a non-transitory computer-readable medium storing computer program instructions.)
Claim 15 is a non-transitory computer-readable medium claim that corresponds to Claim 1 and the remaining limitations are rejected for at least the same reasons therein.
With respect to Claims 5 and 14:
Berti teaches: The computer-implemented method of Claim 1 and the system of Claim 10 respectively, wherein the instructions comprise instructions for identifying and generating recommendations for fixing issues with names of activities of the process, the method further comprising: ([Page 31 Table 11 TQ6; Pages 34-35 Listings 15-16] in which TQ6 discloses the prompt or instruction “Could you identify the root causes of the performance issues in the process?” wherein the aspect of “identifying an issue with names of activities” may lie. Listings 15 and 16 are exemplary illustrations of generated recommendations for fixing issues in the process, such as “streamlining the approval process” in Listing 15 and “optimizing the shipping procedures” in Listing 16.)
identifying the issues with the names of the activities of the process using the large language model based on the textual description of the process model and the instructions; and ([Pages 34-35 Listings 15-16] are exemplary illustrations of a large language model performing root cause analysis, wherein Listing 15 shows that it has identified issues with the approval process “from the process variants and the frequency and performance statistics provided”, and Listing 16 identifies issues with the picking, inventory management, and shipping processes such as lack of staff, items-in-stock, or shipping resources, these issues identified based on event frequency and event duration.)
generating the recommendations for fixing the issues with the activities of the process using the large language model based on the textual description of the process model and the instructions. ([Pages 34-35 Listings 15-16] are exemplary illustrations of a large language model providing generated recommendations for modifications to a process, wherein Listing 15 generates recommendations for streamlining the approval process determined “from the process variants and the frequency and performance statistics provided” and Listing 16 generates recommendations for addressing performance issues in the process based on event frequency and event duration.)
With respect to Claims 6 and 17:
Berti teaches: The computer-implemented method of Claim 1 and the non-transitory computer-readable medium of Claim 15 respectively, wherein the instructions comprise instructions for generating recommendations for improving the process, the method further comprising: ([Page 25 Listing 11] discloses prompt "Can you provide suggestions to improve the process model".)
generating the recommendations for improving the process using the large language model based on the textual description of the process model and the instructions. ([Pages 34-35 Listings 15-16] are exemplary illustrations of generated recommended modifications of the instance of execution that result in conformance of the instance to the process model.)
With respect to Claims 7 and 18:
Berti teaches: The computer-implemented method of Claim 1 and the non-transitory computer-readable medium of Claim 15 respectively, wherein the instance of execution of the process is defined as a sequence of activities of the process. ([Page 11 §2.1 ¶2; Page 17 §2.1.2 ¶1, Listing 6] where Page 11 discusses “procedural and declarative process models. Procedural models focus on the sequence of activities necessary to accomplish a process.”, and Page 17 discloses “sequences of activities that cases may follow in a process” alongside Listing 6 which illustrates a sequence of activities.)
Claim Rejections - 35 USC § 103
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.
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.
Claims 3, 4, 12, and 13 are rejected under 35 U.S.C. 103 as being unpatentable over Berti and Qafari ("Leveraging Large Language Models (LLMs) for Process Mining (Technical Report)"), hereinafter "Berti", in view of Berti, Schuster, and van der Aalst ("Abstractions, Scenarios, and Prompt Definitions for Process Mining with LLMs: A Case Study"), cited by Applicant in the IDS filed 09/28/2023, hereinafter "Schuster".
With respect to Claims 3 and 12:
Berti teaches: The computer-implemented method of Claim 1 and the system of Claim 10 respectively.
Berti does not teach: wherein the instructions comprise instructions for assigning a name to the process, the method further comprising:
generating the name for the process using the large language model based on the textual description of the process model and the instructions.
However, Schuster teaches in the same field of endeavor: wherein the instructions comprise instructions for assigning a name to the process, the method further comprising: ([Page 7 §5.1 “Descriptive Questions: DQ1”] discloses the example prompt "Can you describe the process contained in this data? -GPT-4 should provide the name/category of the process underlying the data".)
generating the name for the process using the large language model based on the textual description of the process model and the instructions. ([Page 7 §5.1 “Descriptive Questions: DQ1”] discloses “GPT-4 should provide the name/category of the process underlying the data”.).
It would have been obvious for one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Berti’s teachings by using a large language model to assign a name for a process as taught by Schuster. One would have been motivated to make this modification in order to improve clarity and interpretation of the invention for further analysis through the large language model.
With respect to Claims 4 and 13:
Berti teaches: The computer-implemented method of Claim 1 and the system of Claim 10 respectively.
Berti does not teach: wherein the instructions comprise further instructions for assigning a name to the instance of execution, the method further comprising:
generating the name for the instance of execution using the large language model based on the textual description of the process model and the instructions.
However, Schuster teaches in the same field of endeavor: wherein the instructions comprise further instructions for assigning a name to the instance of execution, the method further comprising: ([Page 7 §5.1 “Descriptive Questions: DQ1”] discloses the example prompt "Can you describe the process contained in this data? -GPT-4 should provide the name/category of the process underlying the data".)
generating the name for the instance of execution using the large language model based on the textual description of the process model and the instructions ([Page 7 §5.1 “Descriptive Questions: DQ1”] discloses “GPT-4 should provide the name/category of the process underlying the data”.)
It would have been obvious for one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Berti’s teachings by using a large language model to assign a name to the instance of execution as taught by Schuster. One would have been motivated to make this modification in order to improve clarity and interpretation of the invention for further analysis through the large language model.
Claims 8 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Berti in view of de Leoni et al. ("Data-Aware Process Mining: Discovering Decisions in Processes Using Alignments", cited by Applicant in the IDS filed 09/28/2023, hereinafter "de Leoni").
With respect to Claims 8 and 19:
Berti teaches: The computer-implemented method of Claim 1 and the non-transitory computer-readable medium of Claim 15 respectively.
Berti does not teach: wherein the instance of execution is identified as being non-conforming to the process model using a process aligner.”
However, de Leoni teaches in the same field of endeavor: wherein the instance of execution is identified as being non-conforming to the process model using a process aligner.” ([Page 1457 §3 ¶1] discloses aligning the event log and control-flow process model and how to use these alignments for conformance checking.)
It would have been obvious for one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Berti’s teachings by aligning the event log and process model for conformance checking as taught by de Leoni. One would have been motivated to make this modification aiming to use process mining to discover, monitor, and improve real processes by extracting knowledge from event logs. ([de Leoni, Page 1454 §1 ¶1]).
Claims 9 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Berti in view of Iyer et al. (US 2021/0191367 A1), hereinafter "Iyer".
With respect to Claims 9 and 20:
Berti teaches: The computer-implemented method of Claim 1 and the non-transitory computer-readable medium of Claim 15 respectively.
Berti does not teach: wherein the process is an RPA (robotic process automation) workflow executed by one or more RPA robots.
However, Iyer teaches in the same field of endeavor: wherein the process is an RPA (robotic process automation) workflow executed by one or more RPA robots. ([Specification [0024]] discloses how a conductor “orchestrates one or more robots 130 that execute the workflows developed in the designer”.)
It would have been obvious for one of ordinary skill in the art prior to the effective filing date of the claimed invention to modify Berti’s teachings by implementing an RPA workflow executed by a robot as taught by Iyer. One would have been motivated to make this modification as the use of robots would help with remote execution, monitoring, scheduling, and providing support for work queues, as well as automating various systems and applications (Iyer [0026]).
Conclusion
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 BRIAN D. BUI whose telephone number is (571)270-0463. The examiner can normally be reached Monday - Friday 8:00am - 5:00pm.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, ABDULLAH AL KAWSAR can be reached at (571) 270-3169. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/BRIAN D. BUI/Examiner, Art Unit 2127
/ABDULLAH AL KAWSAR/Supervisory Patent Examiner, Art Unit 2127
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