DETAILED ACTION
This communication is in response to the Application filed on February 18, 2025. Claims 1-20 are pending and have been examined.
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 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 an abstract idea without significantly more. All of the claims are method claims (1-10), apparatus/machine claims (11-20) or manufacture claim under (Step 1), but under Step 2A all of these claims recite abstract ideas and specifically mental processes. These mental processes are more particularly recited in claims 1 and 11 as:
performing a similarity analysis to determine a similarity score for the new entry with respect to entries in the ontology…
performing a validation analysis on the new entry to determine a validation score…
adding the new entry to the ontology when the similarity score is below a threshold similarity score and the validation score is above a threshold validation score…
Under Step 2A Prong One, claims 1 and 11 are directed to an abstract idea and specifically a mental process. As detailed above, the steps of performing, adding, etc. may be practically performed in the human mind with the use of a physical aid such as a pen and paper. For example, a human receive a new entry to an ontology tree, assign similarity scores between new entry and existing ontology entries, assign relevancy scores to the new entry if the new entry is not sufficiently similar to any existing ontology entries, and add the entry to the ontology tree if the relevancy score exceeds a predetermined threshold.
Under Step 2A Prong Two, this judicial exception is not integrated into a practical application because claims 1-20 do not recite additional elements that integrate the exception into a practical application. In particular, claims 1 and 11 recite the additional elements of an engine (¶ [0017]), non-transitory storage medium (¶ [0073]), and hardware processors (¶ [0071]). These additional elements are recited at a high level of generality and merely equate to “apply it” or otherwise merely uses a generic computer as a tool to perform an abstract which are not indicative of integration into a practical application as per MPEP 2106.05(f). Further, claims 1 and 11 recite the additional element of “receiving…” which amounts to insignificant extra-solution activities which are not indicative of integration into a practical application as per MPEP 2106.05(g). Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
Under Step 2B, the claims do not recite additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to the integration of the abstract idea into a practical application, the additional elements of using a computer is noted as a general computer {engine (¶ [0017]); non-transitory storage medium (¶ [0073]); hardware processors (¶ [0071])}. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Further, the additional limitations in the claims noted above are directed towards insignificant extra-solution activities. The claims are not patent eligible.
With respect to claims 2 and 12, the claim relates to generating embeddings for new entries. This relates to a human converting a new entry to a vector by hand. No additional limitations are present. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
With respect to claims 3 and 13, the claim relates to comparing new embeddings to existing embeddings stored in a vector database. This relates to a human calculating the cosine similarity between the new entry embedding and existing ontology embeddings by hand. The additional element of a “database” is recited at a high level of generality (¶ [0055]) and merely equates to “apply it” or otherwise merely uses a generic computer as a tool to perform an abstract which are not indicative of integration into a practical application as per MPEP 2106.05(f). No additional limitations are present. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
With respect to claims 4-5 and 14-15, the claim relates to augmenting the most similar entries and embeddings in an ontology when the new entry’s similarity score exceeds a threshold. This relates to a human modifying the most similar entries and embeddings in an ontology tree to include the new entry upon the new entry’s similarity score exceeding a predetermined threshold. The additional element of a “database” is recited at a high level of generality (¶ [0055]) and merely equates to “apply it” or otherwise merely uses a generic computer as a tool to perform an abstract which are not indicative of integration into a practical application as per MPEP 2106.05(f). No additional limitations are present. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
With respect to claims 6 and 16, the claim relates to submitting the new entry to a large language model for analysis. This relates to a human requesting a review of the new entry from a domain expert. The additional element of a “large language model” is recited at a high level of generality (¶ [0002]) and merely equates to “apply it” or otherwise merely uses a generic computer as a tool to perform an abstract which are not indicative of integration into a practical application as per MPEP 2106.05(f). No additional limitations are present. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
With respect to claims 7 and 17, the claim relates to a large language model determining the alignment of the new entry with a domain of the ontology. This relates to the human domain expert determining how relevant the new entry is to the ontology tree. The additional element of a “large language model” is recited at a high level of generality (¶ [0002]) and merely equates to “apply it” or otherwise merely uses a generic computer as a tool to perform an abstract which are not indicative of integration into a practical application as per MPEP 2106.05(f). No additional limitations are present. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
With respect to claims 8 and 18, the claim relates to a large language model evaluating whether a new entry comports with facts or patterns learned by the large language model. This relates to a human domain expert evaluating the new entry based on their personal experience with the domain. The additional element of a “large language model” is recited at a high level of generality (¶ [0002]) and merely equates to “apply it” or otherwise merely uses a generic computer as a tool to perform an abstract which are not indicative of integration into a practical application as per MPEP 2106.05(f). No additional limitations are present. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
With respect to claims 9 and 19, the claim relates to a large language model training on or accessing source documents in a domain. The additional element of a “large language model” is recited at a high level of generality (¶ [0002]) and merely equates to “apply it” or otherwise merely uses a generic computer as a tool to perform an abstract which are not indicative of integration into a practical application as per MPEP 2106.05(f). No additional limitations are present. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
With respect to claims 10 and 20, the claim relates to not including the entry in the ontology if validation analysis fails. This relates to the human discarding the new entry if both similarity analysis and relevancy analysis fails. No additional limitations are present. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
For all of the above reasons, taken alone or in combination, claims 1-20 recite a non-statutory mental process.
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 1-20 are rejected under 35 U.S.C. 103 as obvious over "From Isolated Conversations to Hierarchical Schemas: Dynamic Tree Memory Representation for LLMs" (Rezazadeh et al.) in view of US Patent Publication 20260203306 A1 (Chatterjee et al.).
Claim 1
Regarding claim 1, Rezazadeh et al. disclose a method for performing ontology management, the method comprising:
receiving a new entry (Rezazadeh et al. pg. 4, Section 3.1, Paragraph 2, "To integrate new information, we begin by creating a new node
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with the textual content
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.") at an ontology management engine configured to manage an ontology (Rezazadeh et al. pg. 3, Section 3, Paragraph 1-3, "MemTree represents memory as a tree
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, where
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is the set of directed edges representing parent-child relationships. ... MemTree utilizes this tree-structured representation to dynamically track and update the knowledge exchanged between the user and the LLM." A tree representing parent-child relationship is considered analogous to an ontology);
performing a similarity analysis to determine a similarity score for the new entry with respect to entries in the ontology (Rezazadeh et al. pg. 4, Section 3.1, Paragraph 2, "At each node
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, MemTree evaluates the semantic similarity between the new information
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and the children of the current node in the embedding space.");
[performing a validation analysis on the new entry to determine a validation score when the similarity score is below a threshold similarity score;] and
adding the new entry to the ontology when the similarity score is below a threshold similarity score (Rezazadeh et al. pg. 4, Section 3.1, Paragraph 2, "Create New Leaf Node: If all child nodes’ similarities are below the threshold
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is directly attached as a new leaf node under the current node.") [and the validation score is above a threshold validation score].
Rezazadeh et al. do not explicitly disclose all of validating new entries after similarity analysis fails to meet a threshold.
However, Chatterjee et al. disclose receiving a new entry (Chatterjee et al. ¶ [0014], "The user device 105 may provide, to the validation system 110, information (e.g., documents, knowledge elements, artifacts, and/or the like) to be potentially stored in the knowledge base.") [at an ontology management engine configured to manage an ontology];
performing a similarity analysis to determine a similarity score for the new entry with respect to entries in the [ontology] knowledge base (Chatterjee et al. ¶ [0020]-[0026], "As shown in FIG. 1B, and by reference number 125, the validation system 110 may process the document, with a chunking model, to divide the document into chunks. ... the validation system 110 may compare the vectors created from the chunks and the knowledge base vectors for similarity using a mathematical method, such as a cosine similarity.");
performing a validation analysis on the new entry to determine a validation score when the similarity score is below a threshold similarity score (Chatterjee et al. ¶ [0030]-[0031], "when the similarities fail to satisfy the acceptance threshold, the validation system 110 may optionally validate whether the document is relevant to the knowledge base before discarding the document. ... the validation system 110 may calculate an average of the relevance scores of the chunks as the final score for the document." An acceptance threshold is considered analogous to a threshold similarity score. A final score is considered analogous to a validation score); and
adding the new entry to the [ontology] knowledge base when the similarity score is below a threshold similarity score and the validation score is above a threshold validation score (Chatterjee et al. ¶ [0032], "In some implementations, the validation system 110 may determine that the final score satisfies the relevance threshold. This may indicate that the document is to be added to the knowledge base." A relevance threshold is considered analogous to a threshold validation score. It is noted that failing to satisfy an acceptance threshold (i.e. threshold similarity score) is required to reach this step; see Figures 1A-1G and above citations).
It would have been obvious to a person having ordinary skill in the art before the time of the effective filing date of the claimed invention of the instant application to modify Rezazadeh et al.’s ontology management engine to incorporate Chatterjee et al.’s validation analysis.
The suggestion/motivation for doing so would have been that, “the validation system may conserve computing resources, networking resources, and/or other resources that would have otherwise been consumed by failing to ensure that the knowledge base remains accurate and free from contamination by irrelevant or incorrect information” as noted by the Chatterjee et al. disclosure in paragraph [0013].
Claim 2
Regarding claim 2, the rejection of claim 1 is incorporated.
Rezazadeh et al. further disclose wherein the similarity analysis includes generating a new embedding of the new entry (Rezazadeh et al. pg. 4, Section 3.1, Paragraph 1, "[semantic] evaluation is performed by computing the embedding
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for the new content
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").
Chatterjee et al. further disclose wherein the similarity analysis includes generating a new embedding of the new entry (Chatterjee et al. ¶ [0011], "the validation system may receive a document, and may divide the document into multiple chunks using a chunking model. The validation system may embed the chunks into a multi-dimensional vector space to generate vector representations of the chunks.").
Claim 3
Regarding claim 3, the rejection of claim 2 is incorporated.
Rezazadeh et al. further disclose comparing the new embedding with embeddings of the entries that are stored in a vector database (Rezazadeh et al. pg. 4, Section 3.1, Paragraph 1, "[semantic] evaluation is performed by computing the embedding
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for the new content
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and comparing it to the embeddings of the child nodes
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of the current node
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using cosine similarity.").
Chatterjee et al. further disclose comparing the new embedding with embeddings of the entries that are stored in a vector database (Chatterjee et al. ¶ [0011], "The validation system may compare the vector representations of the chunks with existing vector representations of existing knowledge elements in a knowledge base to determine relevance scores for the chunks").
Claim 4
Regarding claim 4, the rejection of claim 3 is incorporated.
Rezazadeh et al. further disclose when the similarity score is greater than the threshold similarity score, augmenting at least a most similar entry in the ontology to the new entry (Rezazadeh et al. pg. 14, Appendix A.1.1, Algorithm 1, "8: Compute similarity
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for each child
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then 11:
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" Aggregating the content of node
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is considered analogous to augmenting a most similar entry in an ontology to the new entry) and augmenting a most similar embedding in the vector database (Rezazadeh et al. pg. 14, Appendix A.1.1, Algorithm 1, "10: if
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then ... 12:
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").
Claim 5
Regarding claim 5, the rejection of claim 4 is incorporated.
Rezazadeh et al. further disclose supplementing the most similar entry and/or the most similar embedding with additional tags and contexts from the new entry (Rezazadeh et al. pg. 2, Figure 2, "If the new information is semantically akin to an existing leaf node under the current node, it is routed to that node. ... During this process, all ancestor nodes will integrate the new information into the higher-level summaries they maintain." See the top half of Figure 2, which illustrates supplementing an entry (e.g. "Nvidia") that is most similar to input data (e.g. "#Apple") with additional contexts from the new entry ("Nvidia" node is replaced by a "Tech" node that encompasses both "Nvidia" and "Apple"). A "Tech" attribute is considered analogous to additional tags and contexts).
Claim 6
Regarding claim 6, the rejection of claim 1 is incorporated.
Chatterjee et al. further disclose wherein the validation analysis includes submitting the new entry and/or the new embedding to a large language model (Chatterjee et al. ¶ [0030], "As shown in FIG. 1F, and by reference number 155, the validation system 110 may process the chunks, with the LLM ... to determine relevance scores for the chunks and may calculate a final score based on the relevance scores.").
Claim 7
Regarding claim 7, the rejection of claim 6 is incorporated.
Chatterjee et al. further disclose wherein the large language model is configured to determine whether the new entry is aligned with a domain of the ontology and is accurate (Chatterjee et al. ¶ [0019], "For each domain, the validation system 110 may select a few relevant documents and may separate the documents into a training set and a testing set. For each document, the validation system 110 may define LLM prompts whose responses provide a good indication of how well the LLM has learned from the document." ¶ [0079], "process 500 includes utilizing... a large language model (LLM) to validate the chunks and identify deviations from the existing knowledge elements in the knowledge base." Validating chunks and identifying deviations from a knowledge base is considered analogous to determining whether a new entry is aligned with a domain of the knowledge base and is accurate).
Claim 8
Regarding claim 8, the rejection of claim 7 is incorporated.
Chatterjee et al. further disclose wherein the new entry is aligned when the new entry comports with facts or patterns learned by the large language model (Chatterjee et al. ¶ [0079], "process 500 includes utilizing... a large language model (LLM) to ... identify deviations from the existing knowledge elements in the knowledge base." Identifying deviations is considered analogous to determining whether a new entry is comports with patterns learned by a large language model).
Claim 9
Regarding claim 9, the rejection of claim 8 is incorporated.
Chatterjee et al. further disclose wherein the large language model is trained on or has access to source documents associated with the domain (Chatterjee et al. ¶ [0019], "For each domain, the validation system 110 may select a few relevant documents and may separate the documents into a training set and a testing set. For each document, the validation system 110 may define LLM prompts whose responses provide a good indication of how well the LLM has learned from the document.").
Claim 10
Regarding claim 10, the rejection of claim 1 is incorporated.
Chatterjee et al. further disclose wherein, when the validation analysis fails, the new entry is rejected and not included in the ontology (Chatterjee et al. ¶ [0034], "when the final score fails to satisfy the threshold, the validation system 110 may discard the document.") or additional analysis is triggered.
Claim 11
Regarding claim 11, Chatterjee et al. disclose a non-transitory storage medium having stored therein instructions that are executable by one or more hardware processors (Chatterjee et al. ¶ [0070], "a non-transitory computer-readable medium (e.g., the memory 430) may store a set of instructions (e.g., one or more instructions or code) for execution by the processor 420.").
The remaining limitations of claim 11 are similar in scope to that of claim 1 and therefore are rejected for similar reasons as described above.
Claim 12
Regarding claim 12, the rejection of claim 11 is incorporated. The limitations of claim 12 are similar in scope to that of claim 2 and therefore are rejected for similar reasons as described above.
Claim 13
Regarding claim 13, the rejection of claim 12 is incorporated. The limitations of claim 13 are similar in scope to that of claim 3 and therefore are rejected for similar reasons as described above.
Claim 14
Regarding claim 14, the rejection of claim 13 is incorporated. The limitations of claim 14 are similar in scope to that of claim 4 and therefore are rejected for similar reasons as described above.
Claim 15
Regarding claim 15, the rejection of claim 14 is incorporated. The limitations of claim 15 are similar in scope to that of claim 5 and therefore are rejected for similar reasons as described above.
Claim 16
Regarding claim 16, the rejection of claim 11 is incorporated. The limitations of claim 16 are similar in scope to that of claim 6 and therefore are rejected for similar reasons as described above.
Claim 17
Regarding claim 17, the rejection of claim 16 is incorporated. The limitations of claim 17 are similar in scope to that of claim 7 and therefore are rejected for similar reasons as described above.
Claim 18
Regarding claim 18, the rejection of claim 17 is incorporated. The limitations of claim 18 are similar in scope to that of claim 8 and therefore are rejected for similar reasons as described above.
Claim 19
Regarding claim 19, the rejection of claim 18 is incorporated. The limitations of claim 19 are similar in scope to that of claim 9 and therefore are rejected for similar reasons as described above.
Claim 20
Regarding claim 20, the rejection of claim 11 is incorporated. The limitations of claim 20 are similar in scope to that of claim 10 and therefore are rejected for similar reasons as described above.
Reference Cited
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure.
US Patent Publication 20260154320 A1 to Prabhakar et al. discloses using large language models to validate ontologies using factual correctness and ontology domain rules.
US Patent 12141186 B1 to Tomar et al. discloses augmenting taxonomy categories based on threshold similarity scores.
US Patent Publication 20240354322 B1 to Mukherjee et al. discloses generating a classified triple using a large language model and updating an ontology using the classified triple.
Conclusion
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/JACOB B VOGT/ Examiner, Art Unit 2653
/JESSE S PULLIAS/ Primary Examiner, Art Unit 2655 08/21/26
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