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 .
Status of Claims
This action is in reply to the claims filed on 27 February 2025.
Claims 1-20 are currently pending and have been examined.
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., an abstract idea) without significantly more.
Independent claims 1, 12, and 20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claims regard a process that, as drafted under its broadest reasonable interpretation, covers performance of the limitations as a mental process, but for the recitation of generic computer hardware (i.e., an application server (claims 1 and 12), one or more memories storing processor-executable code and one or more processors couples with the one or more memories and individually or collectively operable to execute the code to cause the application server to perform the method (claim 12), non-transitory computer-readable medium storing code for data processing, the code comprising instructions executable by one or more processors to perform the method (claim 20), and LLM (claims 1, 12, and 20)).
In regards to the processing of independent claims 1, 12, and 20, the claimed functionality could be practiced as a mental process in the following manner:
receiving a first request to ingest a document; (a human can mentally with paper receive a document and read it)
generating, based at least in part on the first request and the document, a knowledge graph comprising a plurality of graph triples, each graph triple comprising a first node, a second node, and an edge connecting the first node and the second node, wherein each first node corresponds to a first element type comprised in the document, wherein each second node corresponds to a second element type comprised in the document, and wherein each edge corresponds to a third element type comprised in the document; (a human can draw out a knowledge graph comprising triples using pen and paper)
receiving a second request to generate a generative response; (a human can mentally receive a request to generate a response) and
presenting a response to the second request, the response generated based at least in part on the knowledge graph. (a human can mentally process the knowledge graph to generate a response to a request)
This judicial exception is not integrated into a practical application. Outside of the identified abstract idea, the claimed invention only includes an application server (claims 1 and 12), one or more memories storing processor-executable code and one or more processors couples with the one or more memories and individually or collectively operable to execute the code to cause the application server to perform the method (claim 12), non-transitory computer-readable medium storing code for data processing, the code comprising instructions executable by one or more processors to perform the method (claim 20), and LLM (claims 1, 12, and 20), which amount to no more than mere instructions to implement an otherwise abstract idea using generic components. Note that the computing components here are being used for their ordinary purpose of executing a program to carry out a process (i.e., being used as a tool) instead of being improved as a tool.
Independent claims 1, 12, and 20 do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the above additional element(s) merely use a computer as a tool to perform an abstract idea, which does not render a claim as being significantly more than the judicial exception.
Therefore, claims 1, 12, and 20 are not eligible subject matter under 35 USC 101.
The remaining dependent claims fail to add patent eligible subject matter to their respective parent claims:
Claims 2 and 13 further describe element types in a way that can be mentally understood by a human.
Claims 3 and 14 further describe the request in a way that can be mentally understood by a human.
Claims 4 and 15 further describe the element types in a way that can be mentally understood by a human.
Claims 5 and 16 further describe the response in a way that can be mentally understood by a human.
Claims 6 and 17 further describe the response in a way that can be mentally understood by a human.
Claims 7 and 18 further describe a structure of the graph triples in a way that can be mentally understood by a human drawing a graph with pen and paper.
Claims 8 and 19 further describe the structure of the graph triples in a way that can be mentally understood by a human drawing a graph with pen and paper.
Claim 9 further recites transmitting and receiving information from an LLM. The transmitting and receiving of the information can be mentally understood by a human, and the LLM is being used in its ordinary capacity. The LLM does no more than merely use a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)), which does not integrate the claim(s) into a practical application nor does it render a claim as being significantly more than the abstract idea.
Claim 10 further recites generating graph triples in a way that can be mentally understood by a human with pen and paper. The LLM is being used in its ordinary capacity. The LLM does no more than merely use a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)), which does not integrate the claim(s) into a practical application nor does it render a claim as being significantly more than the abstract idea.
Claim 11 further describes generating the knowledge graph in a way that can be done by a human with pen and paper. The LLM is being used in its ordinary capacity. The LLM does no more than merely use a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)), which does not integrate the claim(s) into a practical application nor does it render a claim as being significantly more than the abstract idea.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ton (US 12,664,191 B1) in view of Bayless (US 20250111192 A1).
Regarding claim 1, Ton teaches a method for data processing at an application server (Col. 60-67 “a server 104”), comprising:
receiving a first request to ingest a document; (Col. 3, ll. 11-26 “Relevant technology standards documents are then subject to natural language processing 204. […] The NLP module 146 splits technology standards documents into sections and divides text into non-overlapping sections based on the topics covered. For example, a technology standards document may be in form of a Portable Document Format (PDF) 20 that is broken into segments or chunks.”; el. 204 of Fig. 2)
generating, using natural language processing (NLP) (Col. 3, ll. 11-26 “Relevant technology standards documents are then subject to natural language processing 204.”; Col. 3, ll. 27-45 “The next operation of FIG. 2 is to construct a knowledge graph 206. The graph module 148 includes instructions executed by processor 130 to construct a knowledge graph as a hierarchical representation of relationships between technology standards document segments.”; el. 204 and 206 of Fig. 2; Fig. 4 shows a graph with nodes (representing the element type of “clause”) connected by edges. The edges represent a relationship (i.e., element type of dependency or inheritance) between two nodes. For example, one edge in Fig. 4 shows 201.12.1.104 is referenced in 201.7.9.2.101)
receiving a second request to generate a generative response with the LLM; (see at least Col. 4, ll. 16-21 “The next operation of FIG. 2 is to prepare LLM prompts 208.”; step 208 of Fig. 2) and
presenting a response to the second request, the response generated by the LLM based at least in part on the knowledge graph. (Col. 6, ll. 1-12 “The requirements module 152 includes instructions executed by processor 130 to use the output from the large language model”; Col. 3, ll. 17-48 “The knowledge graph provides contextual information for a large language model.”; step 210 of Fig. 2)
Ton does not teach
generating, using a large language model (LLM) and based at least in part on the first request and the document, a knowledge graph comprising a plurality of graph triples, each graph triple comprising a first node, a second node, and an edge connecting the first node and the second node, wherein each first node corresponds to a first element type comprised in the document, wherein each second node corresponds to a second element type comprised in the document, and wherein each edge corresponds to a third element type comprised in the document;
However, Bayless teaches:
generating, using a large language model (LLM) and based at least in part on the first request and the document, a knowledge graph comprising a plurality of graph triples, each graph triple comprising a first node, a second node, and an edge connecting the first node and the second node, wherein each first node corresponds to a first element type comprised in the document, wherein each second node corresponds to a second element type comprised in the document, and wherein each edge corresponds to a third element type comprised in the document; (see at least Paragraph [0041] “the knowledge-graph system 104 may act or behave as a graph service where it is able to generate, potentially from scratch, knowledge graphs 122 using one or more LLMs 118.”; Paragraph [0065] “the knowledge graphs 122 and curated knowledge graphs 202 may be graph-like data structures with nodes, edges, attributes, and labels. Nodes in the graphs 122/202 represent entities or concepts (e.g., people places, objects, etc.), the edges represents relationships between the nodes” of Bayless)
This step of Bayless is applicable to the method of Ton as they both share characteristics and capabilities, namely, they are directed to using LLMs and knowledge graphs. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to have modified the graph construction module of Ton to utilize the LLM-driven graph generation as taught by Bayless. One of ordinary skill in the art before the effective filling date of the claimed invention would have been motivated to modify Ton in order to gain various efficiencies over LLM-backed chatbots such as easy debugging (see Abstract of Bayless). Furthermore, doing so would substitute a rigid, rule-based NLP parser with a highly adaptable generative model capable of inferring complex contextual relationship directly into graph triples, yielding the predictable result of a more robust and scalable document-ingestions pipeline.
Regarding claim 2, Ton in view of Bayless teaches the method of claim 1. Ton does not teach:
wherein the first element type comprises a semantic subject, the second element type comprises a semantic object, and the third element type comprises a semantic predicate.
However, Bayless teaches:
wherein the first element type comprises a semantic subject, the second element type comprises a semantic object, and the third element type comprises a semantic predicate. (see at least Paragraph [0065] “For instance, the expression “Fred was born in Germany” has the subject of “Fred,” the predicate of “birthplace,” and the object of “Germany.” In this example, the “birthplace” is an edge in a graph 122/202 and the words “Fred” and “Germany” may be nodes that are connected by the edge, “birthplace.” This is an example of a triplet that may be expressed in the graphs 122/202.” Of Bayless)
The motivation for making this modification to the teachings of Ton is the same as that set forth above, in the rejection of claim 1.
Regarding claim 3, Ton in view of Bayless teaches the method of claim 1. Ton further teaches:
wherein the first request to ingest the document (Col. 3, ll. 11-26 “Relevant technology standards documents are then subject to natural language processing 204. […] The NLP module 146 splits technology standards documents into sections and divides text into non-overlapping sections based on the topics covered. For example, a technology standards document may be in form of a Portable Document Format (PDF) 20 that is broken into segments or chunks.”; el. 204 of Fig. 2)
Ton does not teach:
wherein the first request to ingest the document comprises an indication of the first element type, the second element type, and the third element type.
However, Bayless teaches:
wherein the first request to ingest the document comprises an indication of the first element type, the second element type, and the third element type. (see at least Paragraph [0085] “the prompt 132 may include a request that the LLM 118 generate a truthful answer for the query 128, may include the natural-language query 126, and may further include one or more triple patterns (e.g., a list of triples where some elements are variables). […] The prompt-engineering component 208 may also include some additional information in the prompt to help improve the accuracy of the LLM's response, including […] inferred types of each variable.” Of Bayless)
The motivation for making this modification to the teachings of Ton is the same as that set forth above, in the rejection of claim 1.
Regarding claim 4, Ton in view of Bayless teaches the method of claim 3. Ton further teaches:
wherein the first element type is associated with one or more first entities, the second element type is associated with one or more second entities, the third element type indicates relationships between entities, or any combination thereof. (Examiner notes Fig. 4 shows that the edges indicate a relationship between two nodes, each node representing a clause).
Regarding claim 5, Ton in view of Bayless teaches the method of claim 3. Ton does not teach:
wherein the response comprises a list of entities corresponding to the first element type, a list of entity types corresponding to the list of entities, a list of relationships corresponding to the list of entities, or any combination thereof.
However, Bayless teaches:
wherein the response comprises a list of entities corresponding to the first element type, a list of entity types corresponding to the list of entities, a list of relationships corresponding to the list of entities, or any combination thereof. (see at least Paragraph [0086] “The LLM 118 may then response with a list of assignments 302 to each variable in the triple pattern.” of Bayless; steps 4 and 5 of Fig. 3 of Bayless show how an assignment is translated to a chatbot output containing a list of subjects (i.e. Bill Clinton and George W. Bush) and their relationships to their birth dates.)
The motivation for making this modification to the teachings of Ton is the same as that set forth above, in the rejection of claim 1.
Regarding claim 6, Ton in view of Bayless teaches the method of claim 1. Ton further teaches:
wherein the response comprises a plurality of sentences, each respective sentence of the plurality of sentences corresponding to a respective graph triple of the knowledge graph. (see at least Paragraph [0086] “The LLM 118 may then response with a list of assignments 302 to each variable in the triple pattern.” of Bayless; steps 4 and 5 of Fig. 3 of Bayless show how an assignment is translated to a chatbot output containing a list of subjects (i.e. Bill Clinton and George W. Bush) and their relationships to their birth dates.)
Regarding claim 7, Ton in view of Bayless teaches the method of claim 1. Ton further teaches:
wherein respective first nodes of at least two graph triples are a same first node. (Examiner notes that Fig. 4 shows how multiple nodes can depend on one parent node. For example, 201.7.9.2.101. has multiple children including 201.12.1.104 and 201.12.1)
Regarding claim 8, Ton in view of Bayless teaches the method of claim 1. Ton further teaches:
wherein respective second nodes of at least two graph triples are a same second node. (Examiner notes that Fig. 5 shows that it is possible to have one child node with two parent nodes. This would occur when a clause is references by two other clauses.)
Regarding claim 9, Ton in view of Bayless teaches the method of claim 1. Ton further teaches:
wherein generating the knowledge graph comprises:
transmitting, to NLP (Col. 3, ll. 11-26 “Relevant technology standards documents are then subject to natural language processing 204. […] The NLP module 146 splits technology standards documents into sections and divides text into non-overlapping sections based on the topics covered. For example, a technology standards document may be in form of a Portable Document Format (PDF) 20 that is broken into segments or chunks.”; Col. 3, ll. 27-45 “The next operation of FIG. 2 is to construct a knowledge graph 206. The graph module 148 includes instructions executed by processor 130 to construct a knowledge graph as a hierarchical representation of relationships between technology standards document segments.”; el. 204 and 206 of Fig. 2) and
receiving, from the LLM and based at least in part on the request to generate the knowledge graph, an indication of the knowledge graph. (Col. 6, ll. 1-12 “The requirements module 152 includes instructions executed by processor 130 to use the output from the large language model”; Col. 5, ll. 55-57 “The following is an exemplary prompt form of the output. "Content" is a placeholder for contextual information that was derived from the knowledge graph.”; step 210 of Fig. 2)
Ton does not teach:
transmitting, to the LLM and based at least in part on the first request to ingest the document, a request to generate the knowledge graph.
However, Bayless teaches:
transmitting, to the LLM, a request to generate the knowledge graph. (see at least Paragraph [0041] “the knowledge-graph system 104 may act or behave as a graph service where it is able to generate, potentially from scratch, knowledge graphs 122 using one or more LLMs 118.” Of Bayless)
The motivation for making this modification to the teachings of Ton is the same as that set forth above, in the rejection of claim 1.
Regarding claim 10, Ton in view of Bayless teaches the method of claim 1. Ton does not teach:
wherein generating the knowledge graph comprises:
identifying, via the LLM, one or more instances of the first element type, the second element type, the third element type, or any combination thereof, to generate the plurality of graph triples.
However, Bayless teaches:
wherein generating the knowledge graph comprises:
identifying, via the LLM, one or more instances of the first element type, the second element type, the third element type, or any combination thereof, to generate the plurality of graph triples. (see at least Paragraph [0041] “the knowledge-graph system 104 may act or behave as a graph service where it is able to generate, potentially from scratch, knowledge graphs 122 using one or more LLMs 118.”; Paragraph [0065] “the knowledge graphs 122 and curated knowledge graphs 202 may be graph-like data structures with nodes, edges, attributes, and labels. Nodes in the graphs 122/202 represent entities or concepts (e.g., people places, objects, etc.), the edges represents relationships between the nodes” of Bayless)
The motivation for making this modification to the teachings of Ton is the same as that set forth above, in the rejection of claim 1.
Regarding claim 11, Ton in view of Bayless teaches the method of claim 1. Ton further teaches:
wherein generating the knowledge graph comprises:
identifying, via the LLM, one or more instances of a fourth element type that is different than the first element type, the second element type, and the third element type. (Col. 3, ll. 65- Col. 4, ll. 15 “the rule base may assign indicators to label nodes associated with clauses.”; Col. 6 ll. 1- 12 “The final operation of FIG. 2 is to form probability ratings of requirements to test the product 210. The requirements module 152 includes instructions executed by processor 130 to use the output from the large language model to form probability ratings of requirements to test the product.”; Examiner notes that “a fourth element type” is not explicitly defined by the instant specification. The broadest reasonable interpretation of fourth element type is any type of any variable. A link to a node or edge is not required. There are many possible fourth element types in Ton including probability ratings and node labels. Examiner recommends narrowing this claim to further define “a fourth element type”.)
Claim 12:
Claim 12 is/are directed to a system. Claim 12 recite limitations parallel in nature as those addressed above for claim 1, which are directed towards a method. Claim 12 is/are therefore rejected for the same reasons as set above for claim 1. Claim 12 further recites one or more memories storing processor-executable code; and one or more processors coupled with the one or more memories and individually or collectively operable to execute the code to cause the application server to perform the method (see el. 104 of Fig. 1 of Ton).
Claim 13:
Claim 13 is/are directed to a system. Claim 13 recite limitations parallel in nature as those addressed above for claim 2, which are directed towards a method. Claim 13 is/are therefore rejected for the same reasons as set above for claim 2. Claim 13 further recites one or more memories storing processor-executable code; and one or more processors coupled with the one or more memories and individually or collectively operable to execute the code to cause the application server to perform the method (see el. 104 of Fig. 1 of Ton).
Claim 14:
Claim 14 is/are directed to a system. Claim 14 recite limitations parallel in nature as those addressed above for claim 3, which are directed towards a method. Claim 14 is/are therefore rejected for the same reasons as set above for claim 3. Claim 14 further recites one or more memories storing processor-executable code; and one or more processors coupled with the one or more memories and individually or collectively operable to execute the code to cause the application server to perform the method (see el. 104 of Fig. 1 of Ton).
Claim 15:
Claim 15 is/are directed to a system. Claim 15 recite limitations parallel in nature as those addressed above for claim 4, which are directed towards a method. Claim 15 is/are therefore rejected for the same reasons as set above for claim 4. Claim 15 further recites one or more memories storing processor-executable code; and one or more processors coupled with the one or more memories and individually or collectively operable to execute the code to cause the application server to perform the method (see el. 104 of Fig. 1 of Ton).
Claim 16:
Claim 16 is/are directed to a system. Claim 16 recite limitations parallel in nature as those addressed above for claim 5, which are directed towards a method. Claim 16 is/are therefore rejected for the same reasons as set above for claim 5. Claim 16 further recites one or more memories storing processor-executable code; and one or more processors coupled with the one or more memories and individually or collectively operable to execute the code to cause the application server to perform the method (see el. 104 of Fig. 1 of Ton).
Claim 17:
Claim 17 is/are directed to a system. Claim 17 recite limitations parallel in nature as those addressed above for claim 6, which are directed towards a method. Claim 17 is/are therefore rejected for the same reasons as set above for claim 6. Claim 17 further recites one or more memories storing processor-executable code; and one or more processors coupled with the one or more memories and individually or collectively operable to execute the code to cause the application server to perform the method (see el. 104 of Fig. 1 of Ton).
Claim 18:
Claim 18 is/are directed to a system. Claim 18 recite limitations parallel in nature as those addressed above for claim 7, which are directed towards a method. Claim 18 is/are therefore rejected for the same reasons as set above for claim 7. Claim 18 further recites one or more memories storing processor-executable code; and one or more processors coupled with the one or more memories and individually or collectively operable to execute the code to cause the application server to perform the method (see el. 104 of Fig. 1 of Ton).
Claim 19:
Claim 19 is/are directed to a system. Claim 19 recite limitations parallel in nature as those addressed above for claim 8, which are directed towards a method. Claim 19 is/are therefore rejected for the same reasons as set above for claim 8. Claim 19 further recites one or more memories storing processor-executable code; and one or more processors coupled with the one or more memories and individually or collectively operable to execute the code to cause the application server to perform the method (see el. 104 of Fig. 1 of Ton).
Claim 20:
Claim 20 is/are directed to a system. Claim 20 recite limitations parallel in nature as those addressed above for claim 1, which are directed towards a method. Claim 20 is/are therefore rejected for the same reasons as set above for claim 1. Claim 20 further recites a non-transitory computer-readable medium storing code for data processing, the code comprising instructions executable by one or more processors to perform the method (see Col. 25-40 “non-transitory computer readable storage medium”; el. 104 of Fig. 1 of Ton).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DANIELLE ELIZABETH ZEVITZ whose telephone number is (703)756-1070. The examiner can normally be reached Mo-Th 10am-6pm.
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/DANIELLE ELIZABETH ZEVITZ/Examiner, Art Unit 2655
/ANDREW C FLANDERS/Supervisory Patent Examiner, Art Unit 2655
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