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 .
Claims 1 – 19 are pending in this Office Correspondence.
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 – 19 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.
Step 1: The claims 1 recites a “method for receiving a plurality of scientific documents. . ..; classifying the respective scientific document. . . generating a plurality of text chunks. . . ; generating [using a first ML model] one or more concepts. . . ; generating [using a second ML model] the extended knowledge graph . . . ; storing the extended knowledge graph , , , ;” the claim(s) recites a series of steps and, therefore, is a process.
Step 2A Prong One:
"classifying the respective scientific document. . . . " as drafted recites a mentally performable process as an evaluation or judgement. Please see Instant paragraphs [0020] where one can mentally evaluate to perform a method for database generation for automated [scientific] inquiry and classifying the respective scientific documents.
“generating a plurality of text chunks. . . ; generating one or more concepts. . . ; and generating the extended knowledge graph” as drafted recites a mentally performable process as an evaluation or judgement. Please see Instant paragraph [0020] where one can mentally evaluate to perform a method for database generation for automated [scientific] inquiry and generating a plurality of text chunks from the respective scientific document of a given size, generating concept and generating knowledge graph.
These limitations are processes that, under their broadest reasonable interpretation, cover performance of the limitation in the mind, but for the recitation of generic computer components. That is, other than reciting a "database" or "processor", nothing in the claim element precludes the step from practically being performed in a human mind or with the aid of pen and paper. For example, “classifying” and “generating” in the context of this claim encompasses a user mentally, and with the aid of pen and paper, within the plurality of command sets, generating a plurality of text chunks and “using ML model” to generating concepts and the extended knowledge graph” in order to allowing the researchers to access a unified view of the scientific knowledge contained within the documents.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
Step 2A Prong Two: The judicial exception is not integrated into a practical application. In particular, the claim recites the additional elements “receiving a plurality of scientific documents"; “classifying the respective scientific document” and “structuring the metainformation.” These limitations amount to a data gathering step and a mere generic transmission and presentation of collected and analyzed data which is considered to be insignificant extra solution activity (see MPEP 2106.05(g)).
The limitations represents an extra-solution activity because it is a mere nominal or tangential addition to the claim, a mere generic transmission and presentation of collected and analyzed data. (See 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.
Step 2B: The limitations "receiving”, “classifying” and “structuring” are recognized by the courts as well-understood, routine, and conventional activities when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity (see MPEP 2106.05(d)(II)(iv) Storing and retrieving information in memory, Versata Dev. Group Inc....; Receiving or transmitting data over a network, e.g., using the Internet to gather data, buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); (v) Presenting offers and gathering statistics, OIP Techs., 788 F.3d at 1362-63, 115 USPQ2d at 1092-93). Therefore, the claim is not patent eligible.
Accordingly, claims 10 and 19 are rejected for the same rational under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Therefore, claims 1, 10 and 19 are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Further the limitations in the dependent claims 2 – 9 and 11 – 18, respectively, merely specify the type of the data gathered and analyzed without adding significantly more. Analysis of the dependent claims is shown below.
Claim 2 is dependent on claim 1 and includes all the limitations of claim 1. Therefore, claim 2 recites the same abstract idea of claim 1. The claim recites the additional limitation of “nodes of the extended knowledge graph comprise each of the plurality of text chunks, each concept, and the metainformation, and wherein relationships captured in each document-specific ontology model are mapped to edges of the extended knowledge graph”, which is equivalent to merely saying “apply it”, and amounts to no more than mere instructions to implement the abstract idea on a computer. Mere instructions to apply an exception using a generic computer does not amount to significantly more. Same rationale applies to claim 11, since they also recite limitations that further elaborate on the abstract idea.
Claim 3 is dependent on claim 2 and includes all the limitations of claim 2. Therefore, claim 3 recites the same abstract idea of claim 2. The claim recites the additional limitation of “performing hierarchical clustering on the extended knowledge graph to identify a plurality of community structures, wherein a community structure is a group of nodes densely connected to each other but sparsely connected to other densely connected nodes in a graph”, which further elaborates on the abstract idea, since analyzing of information is a mental process, and therefore, does not meaningfully limits the claim. Same rationale applies to claim 12, since they also recite limitations that further elaborate on the abstract idea.
Claim 4 is dependent on claim 3 and includes all the limitations of claim 3. Therefore, claim 4 recites the same abstract idea of claim 3. The claim recites the additional limitation of “generating, by a third ML model, a summary for each community structure of the plurality of community structures, wherein the summary is indicative of entities in a given community structure and relationships within the given community structure; storing each summary in the graph document database”, which further elaborates on the abstract idea, since analyzing of information is a mental process, and therefore, does not meaningfully limits the claim. Same rationale applies to claim 13, since they also recite limitations that further elaborate on the abstract idea.
Claim 5 is dependent on claim 1 and includes all the limitations of claim 1. Therefore, claim 4 recites the same abstract idea of claim 1. The claim recites the additional limitation of “a large language model (LLM), configured to answer user queries, accesses content of the extended knowledge graph when generating responses”, which further elaborates on the abstract idea, since analyzing of information is a mental process, and therefore, does not meaningfully limits the claim. Same rationale applies to claim 14, since they also recite limitations that further elaborate on the abstract idea.
Claim 6 is dependent on claim 5 and includes all the limitations of claim 5. Therefore, claim 6recites the same abstract idea of claim 5. The claim recites the additional limitation of “the LLM utilizes Retrieval Augmented Generation (RAG) to access the content”, which further elaborates on the abstract idea, since analyzing of information is a mental process, and therefore, does not meaningfully limits the claim. Same rationale applies to claim 15, since they also recite limitations that further elaborate on the abstract idea.
Claim 7 is dependent on claim 1 and includes all the limitations of claim 1. Therefore, claim 7 recites the same abstract idea of claim 1. The claim recites the additional limitation of “de-duplicating matching concepts between multiple scientific documents of the plurality of scientific documents using shared reference dataset”, which further elaborates on the abstract idea, since analyzing of information is a mental process, and therefore, does not meaningfully limits the claim. Same rationale applies to claim 16, since they also recite limitations that further elaborate on the abstract idea.
Claim 8 is dependent on claim 1 and includes all the limitations of claim 1. Therefore, claim 8 recites the same abstract idea of claim 1. The claim recites the additional limitation of “the first ML model and the second ML model are each large language models”, which further elaborates on the abstract idea, since analyzing of information is a mental process, and therefore, does not meaningfully limits the claim. Same rationale applies to claim 17, since they also recite limitations that further elaborate on the abstract idea.
Claim 9 is dependent on claim 1 and includes all the limitations of claim 1. Therefore, claim 9 recites the same abstract idea of claim 1. The claim recites the additional limitation of “the metainformation of the scientific document is extracted using a fourth ML model”, which further elaborates on the abstract idea, since analyzing of information is a mental process, and therefore, does not meaningfully limits the claim. Same rationale applies to claim 18, since they also recite limitations that further elaborate on the abstract idea.
Therefore, claims 1 – 19 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception without significantly more than the abstract idea.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. These references could be used for obviousness type Office action:
Stumpe (USPGPUB 2022/02616668): which involves storing data entities which have whole transcriptome-derived RNA data, clinical findings, disease state diagnostic data, and imaging-derived data in a patient-centric data storage e.g. knowledge graph, where the entities are specific to a patient. Candidate relationships of observational significance are generated between the entities and outcomes events in the data storage. A confidence score is attributed to each of the generated candidate relationships. The generated relationships are ranked based on the attributed confidence scores to classify the relationships into categories reflecting predictive accuracy and clinical actionability.
Duggal (2024/0354567): which involves receiving a request from a client, and tagging the request with interaction-specific embeddings determined by referencing a graph that implements concepts, types, and policies for an automation platform. The tagged request is passed to artificial intelligence (AI). A vector-based output is received from the artificial intelligence, and is deterministically mapped to tags corresponding to the concepts. An action is determined to complete in the automation platform based on the tags. The action is performed in the platform, and a response indicating a result of the action is returned to the client. The artificial intelligence is a large language model, a generative artificial intelligence, a neural network, a natural language processor, a large action model, or other artificial intelligence technology.
Kipersztok (USPGPUB 2007/0018953): which involves providing a domain model representing domain concepts and causal relationships between the domain concepts. A hypothesis is received and a query is related to the domain model. A reasoning analysis is performed according to the formalism and the hypothesis and the query. A prediction is obtained from the hypothesis and an analysis of the domain according to the query. Evidentiary results are searched and extracted from a corpus of text based in part of the hypothesis, query, and prediction, and a summary of the evidentiary results are provided.
Examiner’s Comment:
Claims could be allowable upon overcoming 35 USC 101 rejections.
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SHAHID AL ALAM whose telephone number is (571)272-4030. The examiner can normally be reached M-F 8:00 AM-5:00 PM.
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February 21, 2026
/SHAHID A ALAM/Primary Examiner, Art Unit 2161
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