DETAILED ACTION
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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 03/19/2025 was filed. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
The Supreme Court has long held that “[l]aws of nature, natural phenomena, and abstract ideas are not patentable.” Alice Corp. Pty. Ltd. v. CLS Bank Int’l, 134 S. Ct. 2347, 2354 (2014) (quoting Assoc. for Molecular Pathology v. Myriad Genetics, Inc., 133 S. Ct. 2107, 2116 (2013) (internal quotation marks omitted)). The “abstract ideas” category embodies the longstanding rule that an idea, by itself, is not patentable. Alice Corp., 134S. Ct. at 2355 (quoting Gottschalk v. Benson, 409 U.S. 63, 67 (1972).
In Alice, the Supreme Court sets forth an analytical “framework for distinguishing patents that claim laws of nature, natural phenomena, and abstract ideas [or mental processes ] from those that claim patent-eligible applications of those concepts.” Id. at 2355 (citing Mayo Collaborative Servs. v. Prometheus Labs., Inc., 132 S. Ct. 1289, 1296–97 (2012)). The first step in the analysis is to “determine whether the claims at issue are directed to one of those patent-ineligible concepts.” Id. If the claims are directed to a patent-ineligible concept, the second step in the analysis is to consider the elements of the claims “individually and ‘as an ordered combination’” to determine whether there are additional elements that “‘transform the nature of the claim’ into a patent-eligible application.” Id. (quoting Mayo, 132 S. Ct. at 1298, 1297). In other words, the second step is to “search for an ‘inventive concept’—i.e., an element or combination of elements that is ‘sufficient to ensure that the patent in practice amounts to significantly more than a patent upon the [ineligible concept] itself’”. Id. (brackets in original) (quoting Mayo, 132 S. Ct. at 1294). The prohibition against patenting an abstract idea “‘cannot be circumvented by attempting to limit the use of the formula to a particular technological environment’ or adding ‘insignificant post-solution activity.’” Bilski v. Kappos, 561 U.S. 593, 610–11 (2010) (citation omitted).
Step 1: This part of the eligibility analysis evaluates whether the claim falls within any statutory category. See MPEP 2106.03. Independent Claim 1 recites the method of intent matching of a determined intent of a user input and selectively providing responses based on whether the determined intent is matched with a first list of predefined intents or a second list of select intents. A process is a statutory category of invention. Independent Claim 12 recites a system comprising one or more processors and a memory configured to execute a method similar to Claim 1. A system or apparatus is a Statutory category of invention. Independent claim 18 recites a non-transitory computer-readable medium embodying program code that is executable by one or more processors to cause the one or more processors to perform steps similar to Claim 1. A non-transitory computer-readable medium is a statutory category. Dependent claims 2-11, 13-17 and 19-20 are dependent on claims 1, 12 and 18, respectively, and therefore recite their respective statutory classes.
Step 2A, Prong One: This part of the eligibility analysis evaluates whether the claim recites a judicial exception. As explained in MPEP 2106.04, subsection II, a claim “recites” a judicial exception when the judicial exception is “set forth” or “described” in the claim. In applying the framework set out in Alice, examiner found Applicant’s claims 1, 8 and 15 are directed to a patent-ineligible abstract concept of evaluating consistency of large language model outputs. The steps of Applicant’s claims 1, 8 and 15 are an abstract concept that would fall under the judicial exception of mental processes. Specifically, the claims recite the step of “receiving a natural language text string, wherein the natural language text string comprises a formal rule expressed in natural language.” The recited receiving a text input involves nothing more than the transferring of data. Under broadest reasonable interpretation, the text may be received from a textual note written with pen and paper. Therefore, this step is directed to a mental process. Furthermore, the step of “inputting the natural language text string and a control string into a large language model (LLM), wherein the control string is configured to cause the LLM to generate a formal expression representing the formal rule of the natural language text string” recites a step that is directed to mental process. The claim does not place any limits to how the control string is obtained. The claim further fails to disclose any further detail about the large language model (LLM). The LLM is recited simply as an element receiving two inputs and generating an output from the inputs. Under the broadest reasonable interpretation, the LLM constitutes an additional element to the judicial exception (see Step 2A, Prong Two below for further analysis). Thus, the step is directed to a mental process. Further, the claim recites “outputting, by the large language model, the formal expression”. The recited limitation is directed to nothing more than the transfer of data. Although the large language model is employed to “output” the formal expression, the recited elements are directed to simply transferring the data from one place to another. Thus, under the broadest reasonable interpretation the claim elements are directed to a mental process. Finally, the step of “evaluating a consistency of the formal expression using a test input” fails to provide any limit on how the evaluation is performed. Under broadest reasonable interpretation, the step may be characterized by a human evaluating an expression such as, for example, a mathematical expression, by inputting a test value into the expression to obtain a result. Therefore, the step is directed to a mental process. The claims recite limitations that taken in combination, recite at least a series of mental processes.
Regarding dependent claim 2, the claim recites “wherein the formal expression comprises Boolean logic.” The recited steps are directed to a mental process because the recitation simply describes a general expression, such as a Boolean logic expression, that may be derived by a human with pen and paper.
Regarding dependent claim 3, the claim recites “wherein the formal expression comprises programming language syntax.” The recited steps are directed to a mental process because the recitation simply describes a general expression, such as a programming language syntax, that may be derived, and is commonly written by a human.
Regarding dependent claim 4, the claim recites “create a modified control string based on the consistency of the formal expression; input the natural language text string and the modified control string into the large language model; and output, by the large language model, a second formal expression.” The recited step does not place any limits on how the control string is modified, that is whether the modification is performed by a human or machine, or what is being modified about the control string. Therefore, the recited step is a mental process. Regarding dependent claim 5, the claim recites “wherein the modified control string is configured to configure the large language model to improve the consistency of the second formal expression.” The recites step does not provide any limit description on how the control string is modified to improve the consistency of the second formal expression. Regarding dependent claim 6, the claim recites “wherein the test input comprises a plurality of inputs and a plurality of corresponding outputs for the formal expression.” The recited steps appear to be simply a formatting of the test input, and thus, is a mental process. Regarding dependent claim 7, the claim recites “further comprising a second large language model, and wherein the memory comprises additional executable instructions that, when executed by the one or more processors cause the one or more processors to: generate, by a second large language model, the plurality of inputs and the plurality of corresponding outputs for the formal expression.” The recited steps introduce a second LLM, however, they fail to provide further descriptive language as to how the second LLM is employed. Thus, the second LLM constitutes another additional element and the recited steps are a mental process.
Further dependent claims 9-14 and 16-20 recite similar language as dependent claims 2-7, and thus are analyzed in a similar manner.
Step 2A, Prong Two: This part of the eligibility analysis evaluates whether the claim as a whole integrates the recited judicial exception into a practical application of the exception. This evaluation is performed by (1) identifying whether there are any additional elements recited in the claim beyond the judicial exception, and (2) evaluating those additional elements individually and in combination to determine whether the claim as a whole integrates the exception into a practical application. See MPEP 2106.04(d).
As discussed above, the claims recite “a first large language model” and “a second large language model” as an additional element beyond the judicial exception. The examiner has found, however, that the use of a “large language model” element provides no further detail and is recited at such a high-level of generality that this limitation is merely a post-solution step. Therefore, this step is an insignificant extra-solution activity and does not integrate the judicial exception into a practical application. See MPEP 2106.05(g). Furthermore, independent claim 1 further recites “a memory storing instructions and one or more processors operable to execute the instruction…” and independent claim 15 further recites “when executed by one or more processors, cause one or more computers to perform functions” as additional elements beyond the judicial exception. However, these additional elements do not amount to significantly more than the abstract idea because the additional elements constitute a generic computer environment. Alice, 134 S. Ct. at 2357. The Claims need meaningful limitations that go beyond generally linking the use of an abstract idea to a particular technological environment. Therefore, the steps are all abstract and the Claim as a whole is abstract. “[S]imply appending generic computer functionality to lend speed or efficiency to the performance of an otherwise abstract concept does not meaningfully limit claim scope for purposes of patent eligibility.” CLS Bank, 2013 U.S. App. LEXIS 9493, at *29 (citing Bancorp, 687 F.3d at 1278, and Dealertrack, Inc. v. Huber, 674 F.3d 1315, 1333-34 (Fed. Cir. 2012) (finding that the claimed computer-aided clearinghouse process is a patent-ineligible abstract idea)); SiRF Tech., Inc. v. Int'l Trade Comm'n, 601 F.3d 1319, 1333 (Fed. Cir. 2010) (“In order for the addition of a machine to impose a meaningful limit on the scope of a claim, it must play a significant part in permitting the claimed method to be performed, rather than function solely as an obvious mechanism for permitting a solution to be achieved more quickly, i.e., through the utilization of a computer for performing calculations.”).
Step 2B: This part of the eligibility analysis evaluates whether the claim as a whole amounts 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. See MPEP 2106.05.
At step 2A, prong two, the additional elements of a large language model and the “one or more processors…” and “memory…” were found to be insignificant extra-solution activity and a generic computer environment. At Step 2B, the re-evaluation of the insignificant extra-solution activity consideration takes into account whether or not the extra-solution activity is well understood, routine, and conventional in the field. See MPEP 2106.05(g). Here, the step of providing a large language model is well-understood, routine and conventional, because a large language model is nothing more than an element that is typically embodied as generic programming instructions to perform generation of language. Therefore, this limitation remains insignificant extra-solution activity even upon reconsideration and does not amount to significantly more. 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.
In conclusion, Examiner notes that none of recited steps in Applicant's claims 1-20 refer to a specific machine by reciting structural limitations of any apparatus or to any specific operations that would cause a machine to be the mechanism to perform these steps. Although the claims may be processed by a computing system having a processor, the computing system is merely a general purpose computing system. Therefore, all of the claims 1-20 are abstract.
Claim Rejections - 35 USC § 102
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)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1, 3-8 and 10-20 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Blum (US PG Pub 20250068667).
As per claims 1, 8 and 15, Blum discloses: A system, computer-implemented method of natural language processing, comprising: a first large language model (Blum; Fig. 1, item 201; p. 0022-0023 - The environment 1 includes a large language model (LLM) 201);
a memory storing instructions (Blum; Fig. 1, item 120; p. 0026 - The storage 120 may include volatile and non-volatile memory) and one or more processors operable to execute the instruction (Blum; Fig. 1, item 110; p. 0026 - The controller 110 includes a processor or other compute unit configured to execute instructions stored in the storage 120); a non-transitory computer-readable medium storing the instructions thereon (Blum; p. 0119 – CRM storing non-transitory source code (instructions)) which, when executed by the one or more processors, cause one or more computers to perform functions (Blum; Fig. 1, item 110; p. 0026 - The controller 110 includes a processor or other compute unit configured to execute instructions stored in the storage 120) that include: receiving a natural language text string from an input computing device, wherein the natural language text string comprises a formal rule expressed in natural language (Blum; p. 0031 - the query text 311 is for example a task or instruction (formal rule) for the LLM 201 to carry out. The query text 311 be in the form of a question to be answered by the LLM 201. The query text 311 is in the form of natural language); inputting the natural language text string and a control string into a large language model (LLM) (Blum; p. 0034-0035 - The first part 310 of the prompt 300 effectively corresponds to a normal input query for the LLM 201 (natural language text string), in which analysis of input data 312 is required. The second part 320 is a verification request (control string). The verification request 320 prompts the LLM 201 to provide verification data. That is to say the verification request 320 is a set of instructions included in the prompt that guide the LLM 201 into generating the verification data), wherein the control string is configured to cause the LLM to generate a formal expression representing the formal rule of the natural language text string (Blum; p. 0035 - instructions refers to natural language instructions (e.g. in English) that can be received as input by the LLM 201 and processed thereby, rather than machine-readable instructions. The verification request 320 may also be based on stored template text 123. In some circumstances, the storage 120 stores a plurality of verification request texts 123, and the system 100 selects from amongst the stored texts 123. For example, different query texts 311 and/or different types of input data 312 (as discussed in more detail below) may have different associated verification request texts 123; see also p. 0041 - The verification request 320 takes the form of a set of instructions that prompt the LLM 201 to provide the verification data. The verification request 320 includes a table structure instruction 321 to produce a tracing table which includes a row for each entity value); outputting, by the large language model, the formal expression to an output device (Blum; p. 0047 - In general, the response comprises two parts 510, 520, which are respectively responsive to the first part 310 and second part 320 of the prompt 300. That is to say, the response comprises a first part 510 that contains the response to the query 310. The response also comprises a second part 520 that includes the verification data generated by the LLM 201 in response to the verification data request 320); and evaluating a consistency of the formal expression using a test input (Blum; p. 0053-0060 - The method initially involves a step S701 of creating or instantiating a suitable evaluation context in which the expressions may be evaluated. This involves loading any suitable contextual data into memory of the system. For example, where the input data 312 (test input) is tabular, a data table may be instantiated comprising the input data 312. The pandas library discussed above may be employed for this purpose, with the input data being instantiated as a pandas DataFrame… the expression output is compared to the corresponding value in the row. If comparison reveals that the expression output and the corresponding value match, the value is valid. That is to say, if the expression output and value match, the value is not hallucinated. Conversely, if the expression output and value do not match, the value is determined to be hallucinated).
As per claims 3 and 10, Blum discloses: The system and computer-implemented method of claims 1 and 8, wherein the formal expression comprises programming language syntax (Blum; p. 0045 - In the example, the expressions are Python® expressions. Consequently, each expression is effectively a code snippet that can be executed in a suitable Python environment to provide the output. Particularly, the expressions are pandas expressions. Pandas (https://pandas.pydata.org/) is a Python library for data analysis and manipulation of tabular data. The expressions may also comprise JSON query expressions).
As per claims 4, 11 and 17, Blum discloses: The system, computer-implemented method and non-transitory computer-readable medium of claims 1, 8 and 15, wherein the memory comprises additional executable instructions that, when executed by the one or more processors cause the one or more processors to: create a modified control string based on the consistency of the formal expression; input the natural language text string and the modified control string into the large language model; and output, by the large language model, a second formal expression (Blum; p. 0112 - The method may comprise, in response to the expression output not matching the value included in the query result (based on consistency of the formal expression), generating a prompt including one or more of: the query result; the evaluable expression; the value included in the query result; an indication that the value could not be derived from the input data, and instructions (create a modified control string) that, when processed by the LLM, cause the LLM to generate a corrected query result (output a second formal expression); see also p. 0070-0071).
As per claims 5, 12 and 18, Blum discloses: The system, computer-implemented method and non-transitory computer-readable medium of claims 4, 11 and 17, wherein the modified control string is configured to configure the large language model to improve the consistency of the second formal expression (Blum; p. 0112 - …cause the LLM to generate a corrected query result (improve the consistency of the second formal expression)).
As per claims 6, 13 and 19, Blum discloses: The system, computer-implemented method and non-transitory computer-readable medium of claims 1, 8 and 15, wherein the test input comprises a plurality of inputs and a plurality of corresponding outputs for the formal expression (Blum; p. 0042-0044 - In terms of the content of the tracing table, the verification request 320 includes instructions 322 that cause a column of the tracing table to be populated with values. The values are values that will appear in the query result. In the example, the instruction is to provide the verbatim value from the new context (i.e. from the query response), without surrounding quotes. The verification request 320 further includes instructions 323 that cause the tracing table to be populated with a column including a source for each value. The source will indicate the part of the input data 312 (e.g. a table name) from which the value has been derived. The verification request 320 also includes instructions 324 that cause the tracing table to be populated with a column including an expression for each value (outputs). The expression is evaluable, and thus indicates how the value was derived from the input data 312. If the values have not been hallucinated, the output of the evaluated expression should match the corresponding value (plurality of inputs and a plurality of corresponding outputs). This may be a literal match, or a fuzzy match as discussed in more detail below. Each expressions can be considered proof, in the sense that it is a calculation or other set of computational operations that can be carried out to demonstrate how the value was derived; see also Fig. 6 showing a depiction of the tracing table).
As per claims 7, 14 and 20, Blum discloses:
The system, computer-implemented method and non-transitory computer-readable medium of claims 6, 13 and 19, further comprising a second large language model, and wherein the memory comprises additional executable instructions that, when executed by the one or more processors cause the one or more processors to: generate, by a second large language model, the plurality of inputs and the plurality of corresponding outputs for the formal expression (Blum; p. 0023 - …a variety of LLMs 201 may be employed in the alternative…). As per claim 16, Blum discloses:
The non-transitory computer-readable medium of claim 15, wherein the formal expression comprises programming language syntax or Boolean logic (Blum; p. 0045 - In the example, the expressions are Python® expressions. Consequently, each expression is effectively a code snippet that can be executed in a suitable Python environment to provide the output. Particularly, the expressions are pandas expressions. Pandas (https://pandas.pydata.org/) is a Python library for data analysis and manipulation of tabular data. The expressions may also comprise JSON query expressions).
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.
Claims 2 and 9 are rejected under 35 U.S.C. 103 as being unpatentable over Blum in view of Heller et al. (US Patent 12,067,366; hereinafter “Heller”).
As per claims 2 and 9, Blum discloses: The system and computer-implemented method of claims 1 and 8, upon which clams 2 and 9 depend. Blum, however, fails to disclose wherein the formal expression comprises Boolean logic. Heller does teach wherein the formal expression comprises Boolean logic (Heller; Col. 29, lines 20-33 - A query expansion prompt is created at 1304 based on the query request and a query expansion prompt template. The query expansion prompt template may have one or more fillable portions such as {{text}} that may be filled with text determined based on the query request. The query expansion prompt may include one or more instructions to a large language model. For example, the query expansion prompt may instruct the large language model to generate one or more examples of responses to the query. As another example, the query expansion prompt may instruct the large language model to generate one or more keyword search terms, keyword search queries, Boolean search terms, Boolean search queries, root expansion search terms, and/or combinations thereof. As yet another example, the query expansion prompt may instruct the large language model to format its response in a particular way (using LLM to generate Boolean logic formal expressions)).
Therefore, it would have been obvious to one of ordinary skill in the art to modify the system and computer-implemented method of Blum to include wherein the formal expression comprises Boolean logic, as taught by Heller, in order to provide for reduced overhead associated with prompt instructions while at the same time providing for improved model context to yield an improved response (Heller; Col. 4, lines 10-13).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. The prior art made of record and not relied upon includes:
Heller (US PG Pub 20240242037) teaches: A text generation prompt may be determined based on an input message from a client machine and a designated text generation prompt template. A text generation prompt message including the designated text generation prompt may be sent to a remote text generation modeling system via the communication interface. A text generation prompt response message may be received from the remote text generation modeling system. The text generation prompt response message may include novel text generated by a text generation model implemented at the remote text generation modeling system. The text generation prompt response message may be parsed to generate a response text based on the novel text (Heller; Abstract).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Rodrigo A Chavez whose telephone number is (571)270-0139. The examiner can normally be reached Monday - Friday 9-6 ET.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Richemond Dorvil can be reached at 5712727602. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/RODRIGO A CHAVEZ/Examiner, Art Unit 2658
/RICHEMOND DORVIL/Supervisory Patent Examiner, Art Unit 2658
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