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 .
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are:
“user interface” in claim 30.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Objections
Claim 30 is objected to because of the following informalities:
Line 7 of claim 30 ends with “in which:” and line 8 of claim 30 starts with “in which” (such that claim 30 recites “in which: in which”, and it seems like one of the two consecutive recitations of “in which” should be deleted)
Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1-30 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
As per Claim 1 (and similarly claims 29-30):
The original Specification (i.e. the original Specification of Parent Application 18/301,615, hereafter original Specification, where this application is a continuation, and not a continuation-in-part) does not have written description for (i) retrieving data from a knowledge graph comprising semantic nodes representing entities and links or passages representing relationships; and (ii) representing the retrieved data in a machine readable language distinct from natural language text and using the retrieved data during LLM inference to produce an output (The original Specification does not appear to describe where anything is retrieved from a graph and does not appear to describe where any retrieved data which is used during LLM inference is translated/converted/represented/turned-into UL)
It is also not clear where the original Specification supports claims 2-28 (for claim 28, especially the “programming assistant”, “content creation”, “data analytics”, “legal research”, “education”, “travel”, and “security” applications/services).
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-30 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
As per Claim 1 (and similarly claims 29-30):
“a knowledge graph comprising semantic nodes representing entities and links or passages representing relationships” in lines 5-6 of claim 1 is unclear because it is not clear if:
1. the knowledge graph comprises “semantic nodes”, where the semantic nodes “represent entities and links”, or the knowledge graph comprises “passages representing relationships”
or
2. the knowledge graph comprises “semantic nodes representing entities” and the knowledge graph also comprises “links or passages”, where the “links or passages” “represent[] relationships”
or
3. the knowledge graph comprises “semantic nodes… and links”, where the semantic nodes “represent entities”, or the knowledge graph comprises “passages representing relationships”.
Additionally, as per claim 30:
“the output of the LLM-based system to that prompt” in the last 2 lines of claim 30 lacks antecedent basis (line 3 of claim 30 recites “a response” which is not necessarily a response to “[the] prompt”, and the 4th to last line of claim 30 recites “an output” which is not necessarily an output of the LLM-based system and which is not necessarily an output “to that prompt”).
As per Claim 5 (and similarly claims 6 and 15):
“the machine readable representation” in line 1 of claim 5 lacks explicit antecedent basis (Claim 1 recites where “the retrieved data” is “represent[ed]… in a machine readable language distinct from natural language text” which inherently produces a “machine readable language” “representation” of the retrieved data, but claim 1 does not explicitly recite the phrase “machine readable representation” and it is not entirely clear if Applicant meant to refer to the inherently-produced “machine readable language” “representation” of the retrieved data)
As per Claim 11:
“the nodes and links used to support an output” lacks antecedent basis.
As per Claim 16:
“the representation” lacks explicit antecedent basis (similar issue to the one discussed above pertaining to “the machine readable representation” in claims 5, 6, and 15)
“the declared schema” lacks antecedent basis (claim 15 recites “a declared schema” but claim 16 depends on claim 1 and not on claim 15).
As per Claim 17:
It is not clear if “and a violated constraint” refers to something that is also identified by “a structured error” or is something that is also “return[ed]” (in addition to “a structured error identifying a field path”)
“the representation” lacks explicit antecedent basis (similar issue to the one discussed above pertaining to “the machine readable representation” in claims 5, 6, and 15)
As per Claim 20:
“retrieval filters items use tenets” is grammatically unusual and it is not clear what this phrase is supposed to be (“retrieval filters items us[ing] tenets” perhaps?).
As per Claim 25:
“the structured retrieval expression” lacks antecedent basis (claim 25 depends on claim 1 and not on claim 24)
As per Claim 26:
“the retrieval expression” lacks antecedent basis (claim 26 depends on claim 1 and not on claim 24)
As per Claim 27:
“the output” lacks antecedent basis.
Allowable Subject Matter
The following is a statement of reasons for the indication of allowable subject matter:
As per Claim(s) 1 (and similarly claim[s] 29-30, and consequently claim[s] 2-28 which depend on claim[s] 1), the prior art of record does not teach or suggest the combination of all limitations in claim(s) 1, including (i.e. in combination with the remaining limitations in claim[s] 1) A computer implemented method of improving the accuracy or reliability of an AI system including an LLM (large language model) based system, in which the LLM-based system uses a deep learning model capable of processing natural language and the AI system is capable of generating a sequence of reasoning steps; the method comprising: (i) retrieving data from a knowledge graph comprising semantic nodes representing entities and links or passages representing relationships; and (ii) representing the retrieved data in a machine readable language distinct from natural language text and using the retrieved data during LLM inference to produce an output.
2024/0256841 (provisional 63/442,448 [paragraphs 1, 31 and 33-34] support the cited passages) teaches “The search engine 110 includes a web search module 124, an instant answer search module 125, a knowledge module 128, and a supplemental content search module 130. The web search module 124 is configured to search the web index data store 114 based upon queries received by users, queries generated by the search engine 110 based upon queries received by users, and/or queries generated by the generative model 112 based upon interactions of users with the generative model 112. Similarly, the instant answer search module 126 is configured to search the instant answers data store 116 based upon queries received by users, queries generated by the search engine 110 based upon queries received by users, and/or queries generated by the generative model 112 based upon interactions of users with the generative model 112. The knowledge module 128 is configured to search the knowledge graph data store 118 based upon queries received by users, queries generated by the search engine 110 based upon queries received by users, and/or queries generated by the generative model 112 based upon interactions of users with the generative model 112. Likewise, the supplemental content search module 130 is configured to search the supplemental content data store 120 based upon queries received by users, queries generated by the search engine 110 based upon queries received by users, and/or queries generated by the generative model 112 based upon interactions of users with the generative model 112” (paragraph 34) and “The search engine 110 can generate structured, semi-structured, and/or unstructured data that is representative of content identified by at least one of the modules 124-130. For instance, the search engine 110 generates a JSON document that includes information obtained by the search engine 110 based upon one or more searches performed over the data stores 114-120 (or other data stores). In an example, the search engine 110 generates data that is in a structure/format that is suitable for inclusion in a prompt that is provided to the generative model 112” (paragraph 35) and “The knowledge graph data store 118 includes a knowledge graph, where a knowledge graph includes data structures about entities (people, places, things, etc.) and their relationships to one another, thereby representing relationships between the entities. The search engine 110 can use the knowledge graph in connection with presenting entity cards on a search engine results page (SERP)” (paragraph 32). Paragraph 2 describes where generative models can be LLMs and where generative models generate an output based upon a prompt. This reference does not appear to describe where the entities represented in knowledge graphs are represented by semantic nodes. This reference also does not appear to specifically describe where the generated JSON document represents information obtained/retrieved in JSON (as opposed to where the retrieved knowledge graph data is inserted directly into the JSON document, in which case the JSON document contains the retrieved knowledge graph data itself, and not a JSON representation of the retrieved knowledge graph data).
2024/0256615 and 2024/0256623 teach the same concepts as discussed above pertaining to 2024/0256841.
2022/0261515 teaches “In the knowledge graph, the domain ontology may be represented in semantic form. In semantic form, the nodes (e.g. entities) and structure of the domain ontology, such as relations, are represented in the knowledge graph by a semantic network, or web, of the knowledge graph. The semantic network expresses the relationships (e.g. including dependencies, flows, and hierarchies) between the nodes of the domain ontology. The domain ontology may contain information at different levels of generality or in a hierarchy. For example, the domain ontology may contain information about classes of entities and about specific entities. In this regard, the domain ontology is a structured model of the domain the ontology represents. For example, the engineering domain ontology is a structured model of the engineering domain. In another example, a healthcare domain ontology is a structured model of the healthcare domain” (paragraph 21). This reference describes where, in semantic form, nodes of a knowledge graph are, in some examples, entities (suggesting that the nodes are semantic nodes and where the semantic nodes correspond-to/represent entities) and also where a semantic network expresses relationships between nodes (suggesting where a knowledge graph also includes relationship links). This reference does not appear to describe where data retrieved from the knowledge graph is used by an LLM for inference.
2025/0068942 (LATE filing date) teaches “Runtime agent 462 is configured to obtain the extracted UI content from UI content retrieval service 456 and process the obtained UI content into a consumable format (e.g., Javascript Object Notation (JSON), Extensible Markup Language (XML), screenshot, etc.).” (paragraph 63). This reference does not qualify as prior art.
Double Patenting
For clarity of the record, NO Double Patenting rejections are required between the claims of this application and the claims of the Parent/Sibling applications because the claims of the Parent/Sibling application do not teach or suggest (i) retrieving data from a knowledge graph comprising semantic nodes representing entities and links or passages representing relationships; and (ii) representing the retrieved data in a machine readable language distinct from natural language text and using the retrieved data during LLM inference to produce an output (Claim 10 of Application 19/364,721, Claim 7 of Application 19/383,076, and teaches “in which the engine or tool retrieves data from a knowledge graph comprising semantic nodes representing entities and links/passages representing relationships, and the LLM-based system uses the retrieved data during inference” but not representing the retrieved data in a machine readable language distinct from natural language text)
Conclusion
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EY 7/8/2026
/ERIC YEN/ Primary Examiner, Art Unit 2658
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