DETAILED ACTION
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 12/18/2025 has been entered.
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 .
This action is in response to amendments and remarks filed on 12/18/2025. In the current amendments, claims 1, 8, and 15 are amended. Claims 1, 3-8, 10-15, and 17-20 are pending and have been examined.
In response to amendments and remarks filed on 12/18/2025, the 35 U.S.C. 103 prior art rejections made in the previous office action are withdrawn.
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, 3-8, 10-15, and 17-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Regarding Claim 1,
Claim 1 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 1 is directed to a method, which is directed to a process, one of the statutory categories.
Step 2A Prong One Analysis: The limitations:
“discover new insights from knowledge graphs via utilization of link prediction to detect likely yet previously unknown relationships between entities based upon existing relationships”
“predicting … one or more weighted values of an edge between a pair of entities in a knowledge graph based on one or more candidate statements, each edge associated with a label signifying a particular relationship represented by the edge”
“generating … a confidence score for the one or more predicted weighted values”
“defining the one or more weighted values to represent a predicted, unknown relationship between the pair of entities in the knowledge graph based on existing weighted relationships between one or more of a plurality of entities in the knowledge graph and the predicted weights values”
As drafted, under their broadest reasonable interpretations, cover mental processes (concepts performed in the human mind (including an observation, evaluation, judgement, opinion)) but for the recitation of mere instructions to apply language (See MPEP 2106.05(f)) and insignificant extra-solution activity (See MPEP 2106.05(g)). The above limitations in the context of this claim encompass discovering new insights from a knowledge graph using link prediction to detect new relationships between entities based on existing relationships (corresponds to evaluation and judgement; in particular, a human, with the assistance of pen and paper, can use existing relationships between entities of a knowledge graph to detect new relationships between entities to discover new insights from the knowledge graph); predicting weighted values of an edge between entities in a knowledge graph based on candidate statements, each edge associated with a label signifying a relationship the edge represents (corresponds to evaluation and judgement; in particular, a human, with the assistance of pen and paper, can use candidate statements to predict weighted values of an edge between entities of a knowledge graph); generating a confidence score for the predicted weighted values (corresponds to evaluation and judgement; in particular, a human, with the assistance of pen and paper, can generate a confidence score for the predicted weighted values); and defining the weighted values to represent a predicted, unknown relationship between the entities pair based on existing weighted relationships and the predicted weighted values between entities in the knowledge graph (corresponds to evaluation and judgement; in particular, a human, with the assistance of pen and paper, can use existing weighted relationships between entities in the knowledge graph and the predicted weighted values to define the weighted values to represent a predicted, unknown relationship between the pair of entities).
Step 2A Prong Two Analysis: The judicial exceptions are not integrated into a practical application. In particular, the claim recites additional elements that are mere instructions to apply (See MPEP 2106.05(f)) or insignificant extra-solution activity (See MPEP 2106.05(g)). The limitations:
“a computing system”
“a processor”
“using the trained artificial intelligence model”
As drafted, are additional elements that amount to no more than mere instructions to apply the exception for the abstract ideas. See MPEP 2106.05(f). The limitations:
“receiving heterogeneous data regarding a knowledge graph, the knowledge graph having a plurality of entities and one or more edges, the edges representing relationships between the plurality of entities in the knowledge graph”
“training an artificial intelligence model utilizing the heterogenous data, training the artificial intelligence model involving optimizing a loss function while tuning hyperparameters”
As drafted, are additional elements that correspond to insignificant extra-solution activity. In particular, the additional elements are merely directed towards mere data gathering. See MPEP 2106.05(g). Therefore, the additional elements do not integrate the abstract ideas into a practical application.
Step 2B Analysis: The claim does 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, all of the additional elements are “mere instructions to apply an exception” (I.e. the additional elements describe a computing system, processor, and a generic AI model for applying the abstract ideas) or insignificant extra-solution activity (i.e. receiving data). Furthermore, the “receiving …” limitation is insignificant extra-solution activity that is well-understood, routine, and conventional according to MPEP 2106.05(d) (“The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity… i. Receiving or transmitting data over a network). Additionally, the “training an artificial intelligence model …” limitation is insignificant extra-solution activity that is well-understood, routine, and conventional according to MPEP 2106.05(d) as shown by Ogale et al. (US 10,013,773 B1) in Col. 18, lines 19-25: “the training system uses conventional machine-learning techniques to train the neural network, such as stochastic gradient descent with backpropagation. For example, the training system can backpropagate gradients of a loss function that is based on the determined error to adjust current values of the parameters of the neural network system to optimize the loss function.” Mere instructions to apply an exception cannot provide an inventive concept. The claim is not patent eligible.
Regarding Claim 3,
Claim 3 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 3 is directed to a method, which is directed to a process, one of the statutory categories.
Step 2A Prong One Analysis: The limitations:
“selecting the one or more weighted values of the edge between the pair of entities having a maximum confidence score based on the one or more candidate statements”
As drafted, under their broadest reasonable interpretations, cover mental processes (concepts performed in the human mind (including an observation, evaluation, judgement, opinion)) but for the recitation of mere instructions to apply language (See MPEP 2106.05(f)) and insignificant extra-solution activity (See MPEP 2106.05(g)). The above limitations in the context of this claim encompass selecting weighted values of the edge between entities with a maximum confidence score based on the candidate statements (corresponds to evaluation and judgement; in particular, a human, with the assistance of pen and paper, can select weighted values having a maximum confidence score based on the candidate statements).
Step 2A Prong Two Analysis: The judicial exceptions are not integrated into a practical application. In particular, the claim recites additional elements that are mere instructions to apply (See MPEP 2106.05(f)) or insignificant extra-solution activity (See MPEP 2106.05(g)). The recitation of additional elements in claim 1 of a computing system, processor, and a generic AI model, as drafted, are reciting mere instructions to apply language such that it amounts to no more than mere instructions to apply the exceptions. Furthermore, the “receiving …” and “training …” limitations of claim 1 are additional elements that correspond to insignificant extra-solution activity as mere data gathering. Therefore, the additional elements do not integrate the abstract ideas into a practical application.
Step 2B Analysis: The claim does 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, all of the additional elements are “mere instructions to apply an exception” (I.e. the additional elements describe a computing system, processor, and a generic AI model for applying the abstract ideas) or insignificant extra-solution activity (i.e. receiving data). Furthermore, the “receiving …” limitation is insignificant extra-solution activity that is well-understood, routine, and conventional according to MPEP 2106.05(d) (“The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity… i. Receiving or transmitting data over a network). Additionally, the “training an artificial intelligence model …” limitation is insignificant extra-solution activity that is well-understood, routine, and conventional according to MPEP 2106.05(d) as shown by Ogale et al. (US 10,013,773 B1) in Col. 18, lines 19-25: “the training system uses conventional machine-learning techniques to train the neural network, such as stochastic gradient descent with backpropagation. For example, the training system can backpropagate gradients of a loss function that is based on the determined error to adjust current values of the parameters of the neural network system to optimize the loss function.” Mere instructions to apply an exception cannot provide an inventive concept. The claim is not patent eligible.
Regarding Claim 4,
Claim 4 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 4 is directed to a method, which is directed to a process, one of the statutory categories.
Step 2A Prong One Analysis: The limitations:
“analyzing metadata between a plurality of entities in the knowledge graph, wherein the metadata includes numerical weights of each of the plurality of entities in the knowledge graph”
As drafted, under their broadest reasonable interpretations, cover mental processes (concepts performed in the human mind (including an observation, evaluation, judgement, opinion)) but for the recitation of mere instructions to apply language (See MPEP 2106.05(f)) and insignificant extra-solution activity (See MPEP 2106.05(g)). The above limitations in the context of this claim encompass analyzing metadata between the entities in the knowledge graph, the metadata including numerical weights of each of the entities (corresponds to evaluation and judgement; in particular, a human, with the assistance of pen and paper, can analyze metadata including numerical weights between entities in the knowledge graph).
Step 2A Prong Two Analysis: The judicial exceptions are not integrated into a practical application. In particular, the claim recites additional elements that are mere instructions to apply (See MPEP 2106.05(f)) or insignificant extra-solution activity (See MPEP 2106.05(g)). The recitation of additional elements in claim 1 of a computing system, processor, and a generic AI model, as drafted, are reciting mere instructions to apply language such that it amounts to no more than mere instructions to apply the exceptions. Furthermore, the “receiving …” and “training …” limitations of claim 1 are additional elements that correspond to insignificant extra-solution activity as mere data gathering. Therefore, the additional elements do not integrate the abstract ideas into a practical application.
Step 2B Analysis: The claim does 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, all of the additional elements are “mere instructions to apply an exception” (I.e. the additional elements describe a computing system, processor, and a generic AI model for applying the abstract ideas) or insignificant extra-solution activity (i.e. receiving data). Furthermore, the “receiving …” limitation is insignificant extra-solution activity that is well-understood, routine, and conventional according to MPEP 2106.05(d) (“The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity… i. Receiving or transmitting data over a network). Additionally, the “training an artificial intelligence model …” limitation is insignificant extra-solution activity that is well-understood, routine, and conventional according to MPEP 2106.05(d) as shown by Ogale et al. (US 10,013,773 B1) in Col. 18, lines 19-25: “the training system uses conventional machine-learning techniques to train the neural network, such as stochastic gradient descent with backpropagation. For example, the training system can backpropagate gradients of a loss function that is based on the determined error to adjust current values of the parameters of the neural network system to optimize the loss function.” Mere instructions to apply an exception cannot provide an inventive concept. The claim is not patent eligible.
Regarding Claim 5,
Claim 5 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 5 is directed to a method, which is directed to a process, one of the statutory categories.
Step 2A Prong One Analysis: The limitations:
“incorporating numerical weights of one or more of the plurality of entities in the knowledge graph into knowledge graph embeddings (“KGE”), wherein embedding the numerical weights of the one or more of the plurality of entities of the knowledge graph includes embedding the plurality of entities and relationships into continuous vector spaces”
As drafted, under their broadest reasonable interpretations, cover mental processes (concepts performed in the human mind (including an observation, evaluation, judgement, opinion)) but for the recitation of mere instructions to apply language (See MPEP 2106.05(f)) and insignificant extra-solution activity (See MPEP 2106.05(g)). The above limitations in the context of this claim encompass incorporating numerical weights of the entities in the knowledge graph into knowledge graph embeddings, the embedding including embedding the entities and relationships into continuous vector spaces (corresponds to evaluation and judgement; in particular, a human, with the assistance of pen and paper, can incorporate numerical weights of the entities into knowledge graph embeddings by embedding the entities and relationships into continuous vector spaces).
Step 2A Prong Two Analysis: The judicial exceptions are not integrated into a practical application. In particular, the claim recites additional elements that are mere instructions to apply (See MPEP 2106.05(f)) or insignificant extra-solution activity (See MPEP 2106.05(g)). The recitation of additional elements in claim 1 of a computing system, processor, and a generic AI model, as drafted, are reciting mere instructions to apply language such that it amounts to no more than mere instructions to apply the exceptions. Furthermore, the “receiving …” and “training …” limitations of claim 1 are additional elements that correspond to insignificant extra-solution activity as mere data gathering. Therefore, the additional elements do not integrate the abstract ideas into a practical application.
Step 2B Analysis: The claim does 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, all of the additional elements are “mere instructions to apply an exception” (I.e. the additional elements describe a computing system, processor, and a generic AI model for applying the abstract ideas) or insignificant extra-solution activity (i.e. receiving data). Furthermore, the “receiving …” limitation is insignificant extra-solution activity that is well-understood, routine, and conventional according to MPEP 2106.05(d) (“The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity… i. Receiving or transmitting data over a network). Additionally, the “training an artificial intelligence model …” limitation is insignificant extra-solution activity that is well-understood, routine, and conventional according to MPEP 2106.05(d) as shown by Ogale et al. (US 10,013,773 B1) in Col. 18, lines 19-25: “the training system uses conventional machine-learning techniques to train the neural network, such as stochastic gradient descent with backpropagation. For example, the training system can backpropagate gradients of a loss function that is based on the determined error to adjust current values of the parameters of the neural network system to optimize the loss function.” Mere instructions to apply an exception cannot provide an inventive concept. The claim is not patent eligible.
Regarding Claim 6,
Claim 6 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 6 is directed to a method, which is directed to a process, one of the statutory categories.
Step 2A Prong One Analysis: The limitations:
“generating one or more vector functions for each one of a plurality of entities in the knowledge graph”
As drafted, under their broadest reasonable interpretations, cover mental processes (concepts performed in the human mind (including an observation, evaluation, judgement, opinion)) but for the recitation of mere instructions to apply language (See MPEP 2106.05(f)) and insignificant extra-solution activity (See MPEP 2106.05(g)). The above limitations in the context of this claim encompass generating vector functions for each of the entities in the knowledge graph (corresponds to evaluation and judgement; in particular, a human, with the assistance of pen and paper, can generate vector functions for each entity in the knowledge graph).
Step 2A Prong Two Analysis: The judicial exceptions are not integrated into a practical application. In particular, the claim recites additional elements that are mere instructions to apply (See MPEP 2106.05(f)) or insignificant extra-solution activity (See MPEP 2106.05(g)). The recitation of additional elements in claim 1 of a computing system, processor, and a generic AI model, as drafted, are reciting mere instructions to apply language such that it amounts to no more than mere instructions to apply the exceptions. Furthermore, the “receiving …” and “training …” limitations of claim 1 are additional elements that correspond to insignificant extra-solution activity as mere data gathering. Therefore, the additional elements do not integrate the abstract ideas into a practical application.
Step 2B Analysis: The claim does 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, all of the additional elements are “mere instructions to apply an exception” (I.e. the additional elements describe a computing system, processor, and a generic AI model for applying the abstract ideas) or insignificant extra-solution activity (i.e. receiving data). Furthermore, the “receiving …” limitation is insignificant extra-solution activity that is well-understood, routine, and conventional according to MPEP 2106.05(d) (“The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity… i. Receiving or transmitting data over a network). Additionally, the “training an artificial intelligence model …” limitation is insignificant extra-solution activity that is well-understood, routine, and conventional according to MPEP 2106.05(d) as shown by Ogale et al. (US 10,013,773 B1) in Col. 18, lines 19-25: “the training system uses conventional machine-learning techniques to train the neural network, such as stochastic gradient descent with backpropagation. For example, the training system can backpropagate gradients of a loss function that is based on the determined error to adjust current values of the parameters of the neural network system to optimize the loss function.” Mere instructions to apply an exception cannot provide an inventive concept. The claim is not patent eligible.
Regarding Claim 7,
Claim 7 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 7 is directed to a method, which is directed to a process, one of the statutory categories.
Step 2A Prong One Analysis: The limitations:
“generating one or more vector functions representing a relationship between each one of a plurality of entities in the knowledge graph”
As drafted, under their broadest reasonable interpretations, cover mental processes (concepts performed in the human mind (including an observation, evaluation, judgement, opinion)) but for the recitation of mere instructions to apply language (See MPEP 2106.05(f)) and insignificant extra-solution activity (See MPEP 2106.05(g)). The above limitations in the context of this claim encompass generating vector functions representing a relationship between the entities in the knowledge graph (corresponds to evaluation and judgement; in particular, a human, with the assistance of pen and paper, can generate vector functions representing a relationship between each entity in the knowledge graph).
Step 2A Prong Two Analysis: The judicial exceptions are not integrated into a practical application. In particular, the claim recites additional elements that are mere instructions to apply (See MPEP 2106.05(f)) or insignificant extra-solution activity (See MPEP 2106.05(g)). The recitation of additional elements in claim 1 of a computing system, processor, and a generic AI model, as drafted, are reciting mere instructions to apply language such that it amounts to no more than mere instructions to apply the exceptions. Furthermore, the “receiving …” and “training …” limitations of claim 1 are additional elements that correspond to insignificant extra-solution activity as mere data gathering. Therefore, the additional elements do not integrate the abstract ideas into a practical application.
Step 2B Analysis: The claim does 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, all of the additional elements are “mere instructions to apply an exception” (I.e. the additional elements describe a computing system, processor, and a generic AI model for applying the abstract ideas) or insignificant extra-solution activity (i.e. receiving data). Furthermore, the “receiving …” limitation is insignificant extra-solution activity that is well-understood, routine, and conventional according to MPEP 2106.05(d) (“The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity… i. Receiving or transmitting data over a network). Additionally, the “training an artificial intelligence model …” limitation is insignificant extra-solution activity that is well-understood, routine, and conventional according to MPEP 2106.05(d) as shown by Ogale et al. (US 10,013,773 B1) in Col. 18, lines 19-25: “the training system uses conventional machine-learning techniques to train the neural network, such as stochastic gradient descent with backpropagation. For example, the training system can backpropagate gradients of a loss function that is based on the determined error to adjust current values of the parameters of the neural network system to optimize the loss function.” Mere instructions to apply an exception cannot provide an inventive concept. The claim is not patent eligible.
Regarding Claim 8,
Claim 8 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 8 is directed to a system, which is directed to a machine, one of the statutory categories.
Step 2A Prong One Analysis: The limitations:
“discover new insights from knowledge graphs via utilization of link prediction to detect likely yet previously unknown relationships between entities based upon existing relationships”
“predict … one or more weighted values of an edge between a pair of entities in a knowledge graph based on one or more candidate statements, each edge associated with a label signifying a particular relationship represented by the edge”
“generate … a confidence score for the one or more predicted weighted values”
“defining the one or more weighted values to represent a predicted, unknown relationship between the pair of entities in the knowledge graph based on existing weighted relationships between one or more of a plurality of entities in the knowledge graph and the predicted weighted values”
As drafted, under their broadest reasonable interpretations, cover mental processes (concepts performed in the human mind (including an observation, evaluation, judgement, opinion)) but for the recitation of mere instructions to apply language (See MPEP 2106.05(f)) and insignificant extra-solution activity (See MPEP 2106.05(g)). The above limitations in the context of this claim encompass discovering new insights from a knowledge graph using link prediction to detect new relationships between entities based on existing relationships (corresponds to evaluation and judgement; in particular, a human, with the assistance of pen and paper, can use existing relationships between entities of a knowledge graph to detect new relationships between entities to discover new insights from the knowledge graph); predicting weighted values of an edge between entities in a knowledge graph based on candidate statements, each edge associated with a label signifying a relationship the edge represents (corresponds to evaluation and judgement; in particular, a human, with the assistance of pen and paper, can use candidate statements to predict weighted values of an edge between entities of a knowledge graph); generating a confidence score for the predicted weighted values (corresponds to evaluation and judgement; in particular, a human, with the assistance of pen and paper, can generate a confidence score for the predicted weighted values); and defining the weighted values to represent a predicted, unknown relationship between the entities pair based on existing weighted relationships and the predicted weighted values between entities in the knowledge graph (corresponds to evaluation and judgement; in particular, a human, with the assistance of pen and paper, can use existing weighted relationships between entities in the knowledge graph and the predicted weighted values to define the weighted values to represent a predicted, unknown relationship between the pair of entities).
Step 2A Prong Two Analysis: The judicial exceptions are not integrated into a practical application. In particular, the claim recites additional elements that are mere instructions to apply (See MPEP 2106.05(f)) or insignificant extra-solution activity (See MPEP 2106.05(g)). The limitations:
“one or more computers”
“using the trained artificial intelligence model”
As drafted, are additional elements that amount to no more than mere instructions to apply the exception for the abstract ideas. See MPEP 2106.05(f). The limitations:
“receive heterogeneous data regarding a knowledge graph, the knowledge graph having a plurality of entities and one or more edges, the edges representing relationships between the plurality of entities in the knowledge graph”
“train an artificial intelligence model utilizing the heterogenous data, training the artificial intelligence model involving optimizing a loss function while tuning hyperparameters”
As drafted, are additional elements that correspond to insignificant extra-solution activity. In particular, the additional elements are merely directed towards mere data gathering. See MPEP 2106.05(g). Therefore, the additional elements do not integrate the abstract ideas into a practical application.
Step 2B Analysis: The claim does 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, all of the additional elements are “mere instructions to apply an exception” (I.e. the additional elements describe computers and a generic AI model for applying the abstract ideas) or insignificant extra-solution activity (i.e. receiving data). Furthermore, the “receive …” limitation is insignificant extra-solution activity that is well-understood, routine, and conventional according to MPEP 2106.05(d) (“The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity… i. Receiving or transmitting data over a network). Additionally, the “train an artificial intelligence model …” limitation is insignificant extra-solution activity that is well-understood, routine, and conventional according to MPEP 2106.05(d) as shown by Ogale et al. (US 10,013,773 B1) in Col. 18, lines 19-25: “the training system uses conventional machine-learning techniques to train the neural network, such as stochastic gradient descent with backpropagation. For example, the training system can backpropagate gradients of a loss function that is based on the determined error to adjust current values of the parameters of the neural network system to optimize the loss function.” Mere instructions to apply an exception cannot provide an inventive concept. The claim is not patent eligible.
Regarding Claim 10,
Claim 10 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 10 is directed to a system, which is directed to a machine, one of the statutory categories.
Step 2A Prong One Analysis: The limitations:
“select the one or more weighted values of the edge between the pair of entities having a maximum confidence score based on the one or more candidate statements”
As drafted, under their broadest reasonable interpretations, cover mental processes (concepts performed in the human mind (including an observation, evaluation, judgement, opinion)) but for the recitation of mere instructions to apply language (See MPEP 2106.05(f)) and insignificant extra-solution activity (See MPEP 2106.05(g)). The above limitations in the context of this claim encompass selecting weighted values of the edge between entities with a maximum confidence score based on the candidate statements (corresponds to evaluation and judgement; in particular, a human, with the assistance of pen and paper, can select weighted values having a maximum confidence score based on the candidate statements).
Step 2A Prong Two Analysis: The judicial exceptions are not integrated into a practical application. In particular, the claim recites additional elements that are mere instructions to apply (See MPEP 2106.05(f)) or insignificant extra-solution activity (See MPEP 2106.05(g)). The recitation of additional elements in claim 8 of a computing system, processor, and a generic AI model, as drafted, are reciting mere instructions to apply language such that it amounts to no more than mere instructions to apply the exceptions. Furthermore, the “receive …” and “train …” limitations of claim 8 are additional elements that correspond to insignificant extra-solution activity as mere data gathering. Therefore, the additional elements do not integrate the abstract ideas into a practical application.
Step 2B Analysis: The claim does 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, all of the additional elements are “mere instructions to apply an exception” (I.e. the additional elements describe computers and a generic AI model for applying the abstract ideas) or insignificant extra-solution activity (i.e. receiving data). Furthermore, the “receive …” limitation is insignificant extra-solution activity that is well-understood, routine, and conventional according to MPEP 2106.05(d) (“The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity… i. Receiving or transmitting data over a network). Additionally, the “train an artificial intelligence model …” limitation is insignificant extra-solution activity that is well-understood, routine, and conventional according to MPEP 2106.05(d) as shown by Ogale et al. (US 10,013,773 B1) in Col. 18, lines 19-25: “the training system uses conventional machine-learning techniques to train the neural network, such as stochastic gradient descent with backpropagation. For example, the training system can backpropagate gradients of a loss function that is based on the determined error to adjust current values of the parameters of the neural network system to optimize the loss function.” Mere instructions to apply an exception cannot provide an inventive concept. The claim is not patent eligible.
Regarding Claim 11,
Claim 11 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 11 is directed to a system, which is directed to a machine, one of the statutory categories.
Step 2A Prong One Analysis: The limitations:
“analyze metadata between a plurality of entities in the knowledge graph, wherein the metadata includes numerical weights of each of the plurality of entities in the knowledge graph”
As drafted, under their broadest reasonable interpretations, cover mental processes (concepts performed in the human mind (including an observation, evaluation, judgement, opinion)) but for the recitation of mere instructions to apply language (See MPEP 2106.05(f)) and insignificant extra-solution activity (See MPEP 2106.05(g)). The above limitations in the context of this claim encompass analyzing metadata between the entities in the knowledge graph, the metadata including numerical weights of each of the entities (corresponds to evaluation and judgement; in particular, a human, with the assistance of pen and paper, can analyze metadata including numerical weights between entities in the knowledge graph).
Step 2A Prong Two Analysis: The judicial exceptions are not integrated into a practical application. In particular, the claim recites additional elements that are mere instructions to apply (See MPEP 2106.05(f)) or insignificant extra-solution activity (See MPEP 2106.05(g)). The recitation of additional elements in claim 8 of a computing system, processor, and a generic AI model, as drafted, are reciting mere instructions to apply language such that it amounts to no more than mere instructions to apply the exceptions. Furthermore, the “receive …” and “train …” limitations of claim 8 are additional elements that correspond to insignificant extra-solution activity as mere data gathering. Therefore, the additional elements do not integrate the abstract ideas into a practical application.
Step 2B Analysis: The claim does 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, all of the additional elements are “mere instructions to apply an exception” (I.e. the additional elements describe computers and a generic AI model for applying the abstract ideas) or insignificant extra-solution activity (i.e. receiving data). Furthermore, the “receive …” limitation is insignificant extra-solution activity that is well-understood, routine, and conventional according to MPEP 2106.05(d) (“The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity… i. Receiving or transmitting data over a network). Additionally, the “train an artificial intelligence model …” limitation is insignificant extra-solution activity that is well-understood, routine, and conventional according to MPEP 2106.05(d) as shown by Ogale et al. (US 10,013,773 B1) in Col. 18, lines 19-25: “the training system uses conventional machine-learning techniques to train the neural network, such as stochastic gradient descent with backpropagation. For example, the training system can backpropagate gradients of a loss function that is based on the determined error to adjust current values of the parameters of the neural network system to optimize the loss function.” Mere instructions to apply an exception cannot provide an inventive concept. The claim is not patent eligible.
Regarding Claim 12,
Claim 12 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 12 is directed to a system, which is directed to a machine, one of the statutory categories.
Step 2A Prong One Analysis: The limitations:
“incorporate numerical weights of one or more of the plurality of entities in the knowledge graph into knowledge graph embeddings (“KGE”), wherein embedding the numerical weights of the one or more of the plurality of entities of the knowledge graph includes embedding the plurality of entities and relationships into continuous vector spaces”
As drafted, under their broadest reasonable interpretations, cover mental processes (concepts performed in the human mind (including an observation, evaluation, judgement, opinion)) but for the recitation of mere instructions to apply language (See MPEP 2106.05(f)) and insignificant extra-solution activity (See MPEP 2106.05(g)). The above limitations in the context of this claim encompass incorporating numerical weights of the entities in the knowledge graph into knowledge graph embeddings, the embedding including embedding the entities and relationships into continuous vector spaces (corresponds to evaluation and judgement; in particular, a human, with the assistance of pen and paper, can incorporate numerical weights of the entities into knowledge graph embeddings by embedding the entities and relationships into continuous vector spaces).
Step 2A Prong Two Analysis: The judicial exceptions are not integrated into a practical application. In particular, the claim recites additional elements that are mere instructions to apply (See MPEP 2106.05(f)) or insignificant extra-solution activity (See MPEP 2106.05(g)). The recitation of additional elements in claim 8 of a computing system, processor, and a generic AI model, as drafted, are reciting mere instructions to apply language such that it amounts to no more than mere instructions to apply the exceptions. Furthermore, the “receive …” and “train …” limitations of claim 8 are additional elements that correspond to insignificant extra-solution activity as mere data gathering. Therefore, the additional elements do not integrate the abstract ideas into a practical application.
Step 2B Analysis: The claim does 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, all of the additional elements are “mere instructions to apply an exception” (I.e. the additional elements describe computers and a generic AI model for applying the abstract ideas) or insignificant extra-solution activity (i.e. receiving data). Furthermore, the “receive …” limitation is insignificant extra-solution activity that is well-understood, routine, and conventional according to MPEP 2106.05(d) (“The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity… i. Receiving or transmitting data over a network). Additionally, the “train an artificial intelligence model …” limitation is insignificant extra-solution activity that is well-understood, routine, and conventional according to MPEP 2106.05(d) as shown by Ogale et al. (US 10,013,773 B1) in Col. 18, lines 19-25: “the training system uses conventional machine-learning techniques to train the neural network, such as stochastic gradient descent with backpropagation. For example, the training system can backpropagate gradients of a loss function that is based on the determined error to adjust current values of the parameters of the neural network system to optimize the loss function.” Mere instructions to apply an exception cannot provide an inventive concept. The claim is not patent eligible.
Regarding Claim 13,
Claim 13 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 13 is directed to a system, which is directed to a machine, one of the statutory categories.
Step 2A Prong One Analysis: The limitations:
“generate one or more vector functions for each one of a plurality of entities in the knowledge graph”
As drafted, under their broadest reasonable interpretations, cover mental processes (concepts performed in the human mind (including an observation, evaluation, judgement, opinion)) but for the recitation of mere instructions to apply language (See MPEP 2106.05(f)) and insignificant extra-solution activity (See MPEP 2106.05(g)). The above limitations in the context of this claim encompass generating vector functions for each of the entities in the knowledge graph (corresponds to evaluation and judgement; in particular, a human, with the assistance of pen and paper, can generate vector functions for each entity in the knowledge graph).
Step 2A Prong Two Analysis: The judicial exceptions are not integrated into a practical application. In particular, the claim recites additional elements that are mere instructions to apply (See MPEP 2106.05(f)) or insignificant extra-solution activity (See MPEP 2106.05(g)). The recitation of additional elements in claim 8 of a computing system, processor, and a generic AI model, as drafted, are reciting mere instructions to apply language such that it amounts to no more than mere instructions to apply the exceptions. Furthermore, the “receive …” and “train …” limitations of claim 8 are additional elements that correspond to insignificant extra-solution activity as mere data gathering. Therefore, the additional elements do not integrate the abstract ideas into a practical application.
Step 2B Analysis: The claim does 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, all of the additional elements are “mere instructions to apply an exception” (I.e. the additional elements describe computers and a generic AI model for applying the abstract ideas) or insignificant extra-solution activity (i.e. receiving data). Furthermore, the “receive …” limitation is insignificant extra-solution activity that is well-understood, routine, and conventional according to MPEP 2106.05(d) (“The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity… i. Receiving or transmitting data over a network). Additionally, the “train an artificial intelligence model …” limitation is insignificant extra-solution activity that is well-understood, routine, and conventional according to MPEP 2106.05(d) as shown by Ogale et al. (US 10,013,773 B1) in Col. 18, lines 19-25: “the training system uses conventional machine-learning techniques to train the neural network, such as stochastic gradient descent with backpropagation. For example, the training system can backpropagate gradients of a loss function that is based on the determined error to adjust current values of the parameters of the neural network system to optimize the loss function.” Mere instructions to apply an exception cannot provide an inventive concept. The claim is not patent eligible.
Regarding Claim 14,
Claim 14 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 14 is directed to a system, which is directed to a machine, one of the statutory categories.
Step 2A Prong One Analysis: The limitations:
“generate one or more vector functions representing a relationship between each one of a plurality of entities in the knowledge graph”
As drafted, under their broadest reasonable interpretations, cover mental processes (concepts performed in the human mind (including an observation, evaluation, judgement, opinion)) but for the recitation of mere instructions to apply language (See MPEP 2106.05(f)) and insignificant extra-solution activity (See MPEP 2106.05(g)). The above limitations in the context of this claim encompass generating vector functions representing a relationship between the entities in the knowledge graph (corresponds to evaluation and judgement; in particular, a human, with the assistance of pen and paper, can generate vector functions representing a relationship between each entity in the knowledge graph).
Step 2A Prong Two Analysis: The judicial exceptions are not integrated into a practical application. In particular, the claim recites additional elements that are mere instructions to apply (See MPEP 2106.05(f)) or insignificant extra-solution activity (See MPEP 2106.05(g)). The recitation of additional elements in claim 8 of a computing system, processor, and a generic AI model, as drafted, are reciting mere instructions to apply language such that it amounts to no more than mere instructions to apply the exceptions. Furthermore, the “receive …” and “train …” limitations of claim 8 are additional elements that correspond to insignificant extra-solution activity as mere data gathering. Therefore, the additional elements do not integrate the abstract ideas into a practical application.
Step 2B Analysis: The claim does 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, all of the additional elements are “mere instructions to apply an exception” (I.e. the additional elements describe computers and a generic AI model for applying the abstract ideas) or insignificant extra-solution activity (i.e. receiving data). Furthermore, the “receive …” limitation is insignificant extra-solution activity that is well-understood, routine, and conventional according to MPEP 2106.05(d) (“The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity… i. Receiving or transmitting data over a network). Additionally, the “train an artificial intelligence model …” limitation is insignificant extra-solution activity that is well-understood, routine, and conventional according to MPEP 2106.05(d) as shown by Ogale et al. (US 10,013,773 B1) in Col. 18, lines 19-25: “the training system uses conventional machine-learning techniques to train the neural network, such as stochastic gradient descent with backpropagation. For example, the training system can backpropagate gradients of a loss function that is based on the determined error to adjust current values of the parameters of the neural network system to optimize the loss function.” Mere instructions to apply an exception cannot provide an inventive concept. The claim is not patent eligible.
Regarding Claim 15,
Claim 15 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 15 is directed to a computer program product comprising one or more computer readable storage media, which is directed to an article of manufacture, one of the statutory categories.
Step 2A Prong One Analysis: The limitations:
“discover new insights from knowledge graphs via utilization of link prediction to detect likely yet previously unknown relationships between entities based upon existing relationships”
“predict … one or more weighted values of an edge between a pair of entities in a knowledge graph based on one or more candidate statements, each edge associated with a label signifying a particular relationship represented by the edge”
“generate a confidence score for the one or more predicted weighted values”
“define the one or more weighted values to represent a predicted, unknown relationship between the pair of entities in the knowledge graph based on existing weighted relationships between one or more of a plurality of entities in the knowledge graph and the predicted weighted values”
As drafted, under their broadest reasonable interpretations, cover mental processes (concepts performed in the human mind (including an observation, evaluation, judgement, opinion)) but for the recitation of mere instructions to apply language (See MPEP 2106.05(f)) and insignificant extra-solution activity (See MPEP 2106.05(g)). The above limitations in the context of this claim encompass discovering new insights from a knowledge graph using link prediction to detect new relationships between entities based on existing relationships (corresponds to evaluation and judgement; in particular, a human, with the assistance of pen and paper, can use existing relationships between entities of a knowledge graph to detect new relationships between entities to discover new insights from the knowledge graph); predicting weighted values of an edge between entities in a knowledge graph based on candidate statements, each edge associated with a label signifying a relationship the edge represents (corresponds to evaluation and judgement; in particular, a human, with the assistance of pen and paper, can use candidate statements to predict weighted values of an edge between entities of a knowledge graph); generating a confidence score for the predicted weighted values (corresponds to evaluation and judgement; in particular, a human, with the assistance of pen and paper, can generate a confidence score for the predicted weighted values); and defining the weighted values to represent a predicted, unknown relationship between the entities pair based on existing weighted relationships and the predicted weighted values between entities in the knowledge graph (corresponds to evaluation and judgement; in particular, a human, with the assistance of pen and paper, can use existing weighted relationships between entities in the knowledge graph and the predicted weighted values to define the weighted values to represent a predicted, unknown relationship between the pair of entities).
Step 2A Prong Two Analysis: The judicial exceptions are not integrated into a practical application. In particular, the claim recites additional elements that are mere instructions to apply (See MPEP 2106.05(f)) or insignificant extra-solution activity (See MPEP 2106.05(g)). The limitations:
“one or more computer readable storage media”
“program instructions”
“using the trained artificial intelligence model”
As drafted, are additional elements that amount to no more than mere instructions to apply the exception for the abstract ideas. See MPEP 2106.05(f). The limitations:
“receive heterogeneous data regarding a knowledge graph, the knowledge graph having a plurality of entities and one or more edges, the edges representing relationships between the plurality of entities in the knowledge graph”
“train an artificial intelligence model utilizing the heterogenous data, training the artificial intelligence model involving optimizing a loss function while tuning hyperparameters”
As drafted, are additional elements that correspond to insignificant extra-solution activity. In particular, the additional elements are merely directed towards mere data gathering. See MPEP 2106.05(g). Therefore, the additional elements do not integrate the abstract ideas into a practical application.
Step 2B Analysis: The claim does 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, all of the additional elements are “mere instructions to apply an exception” (I.e. the additional elements describe computer readable storage media, program instructions, and a generic AI model for applying the abstract ideas) or insignificant extra-solution activity (i.e. receiving data). Furthermore, the “receive …” limitation is insignificant extra-solution activity that is well-understood, routine, and conventional according to MPEP 2106.05(d) (“The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity… i. Receiving or transmitting data over a network). Additionally, the “train an artificial intelligence model …” limitation is insignificant extra-solution activity that is well-understood, routine, and conventional according to MPEP 2106.05(d) as shown by Ogale et al. (US 10,013,773 B1) in Col. 18, lines 19-25: “the training system uses conventional machine-learning techniques to train the neural network, such as stochastic gradient descent with backpropagation. For example, the training system can backpropagate gradients of a loss function that is based on the determined error to adjust current values of the parameters of the neural network system to optimize the loss function.” Mere instructions to apply an exception cannot provide an inventive concept. The claim is not patent eligible.
Regarding Claim 17,
Claim 17 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 17 is directed to a computer program product comprising one or more computer readable storage media, which is directed to an article of manufacture, one of the statutory categories.
Step 2A Prong One Analysis: The limitations:
“select the one or more weighted values of the edge between the pair of entities having a maximum confidence score based on the one or more candidate statements”
As drafted, under their broadest reasonable interpretations, cover mental processes (concepts performed in the human mind (including an observation, evaluation, judgement, opinion)) but for the recitation of mere instructions to apply language (See MPEP 2106.05(f)) and insignificant extra-solution activity (See MPEP 2106.05(g)). The above limitations in the context of this claim encompass selecting weighted values of the edge between entities with a maximum confidence score based on the candidate statements (corresponds to evaluation and judgement; in particular, a human, with the assistance of pen and paper, can select weighted values having a maximum confidence score based on the candidate statements).
Step 2A Prong Two Analysis: The judicial exceptions are not integrated into a practical application. In particular, the claim recites additional elements that are mere instructions to apply (See MPEP 2106.05(f)) or insignificant extra-solution activity (See MPEP 2106.05(g)). The recitation of additional elements in claim 15 of a computing system, processor, and a generic AI model, as drafted, are reciting mere instructions to apply language such that it amounts to no more than mere instructions to apply the exceptions. Furthermore, the “receive …” and “train …” limitations of claim 15 are additional elements that correspond to insignificant extra-solution activity as mere data gathering. Therefore, the additional elements do not integrate the abstract ideas into a practical application.
Step 2B Analysis: The claim does 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, all of the additional elements are “mere instructions to apply an exception” (I.e. the additional elements describe computer readable storage media, program instructions, and a generic AI model for applying the abstract ideas) or insignificant extra-solution activity (i.e. receiving data). Furthermore, the “receive …” limitation is insignificant extra-solution activity that is well-understood, routine, and conventional according to MPEP 2106.05(d) (“The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity… i. Receiving or transmitting data over a network). Additionally, the “train an artificial intelligence model …” limitation is insignificant extra-solution activity that is well-understood, routine, and conventional according to MPEP 2106.05(d) as shown by Ogale et al. (US 10,013,773 B1) in Col. 18, lines 19-25: “the training system uses conventional machine-learning techniques to train the neural network, such as stochastic gradient descent with backpropagation. For example, the training system can backpropagate gradients of a loss function that is based on the determined error to adjust current values of the parameters of the neural network system to optimize the loss function.” Mere instructions to apply an exception cannot provide an inventive concept. The claim is not patent eligible.
Regarding Claim 18,
Claim 18 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 18 is directed to a computer program product comprising one or more computer readable storage media, which is directed to an article of manufacture, one of the statutory categories.
Step 2A Prong One Analysis: The limitations:
“analyze metadata between a plurality of entities in the knowledge graph, wherein the metadata includes numerical weights of each of the plurality of entities in the knowledge graph”
“incorporate the numerical weights of one or more of the plurality of entities in the knowledge graph into knowledge graph embeddings (“KGE”), wherein embedding the numerical weights of the one or more of the plurality of entities of the knowledge graph includes embedding the plurality of entities and relationships into continuous vector spaces”
As drafted, under their broadest reasonable interpretations, cover mental processes (concepts performed in the human mind (including an observation, evaluation, judgement, opinion)) but for the recitation of mere instructions to apply language (See MPEP 2106.05(f)) and insignificant extra-solution activity (See MPEP 2106.05(g)). The above limitations in the context of this claim encompass analyzing metadata between the entities in the knowledge graph, the metadata including numerical weights of each of the entities (corresponds to evaluation and judgement; in particular, a human, with the assistance of pen and paper, can analyze metadata including numerical weights between entities in the knowledge graph); and incorporating numerical weights of the entities in the knowledge graph into knowledge graph embeddings, the embedding including embedding the entities and relationships into continuous vector spaces (corresponds to evaluation and judgement; in particular, a human, with the assistance of pen and paper, can incorporate numerical weights of the entities into knowledge graph embeddings by embedding the entities and relationships into continuous vector spaces).
Step 2A Prong Two Analysis: The judicial exceptions are not integrated into a practical application. In particular, the claim recites additional elements that are mere instructions to apply (See MPEP 2106.05(f)) or insignificant extra-solution activity (See MPEP 2106.05(g)). The recitation of additional elements in claim 15 of a computing system, processor, and a generic AI model, as drafted, are reciting mere instructions to apply language such that it amounts to no more than mere instructions to apply the exceptions. Furthermore, the “receive …” and “train …” limitations of claim 15 are additional elements that correspond to insignificant extra-solution activity as mere data gathering. Therefore, the additional elements do not integrate the abstract ideas into a practical application.
Step 2B Analysis: The claim does 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, all of the additional elements are “mere instructions to apply an exception” (I.e. the additional elements describe computer readable storage media, program instructions, and a generic AI model for applying the abstract ideas) or insignificant extra-solution activity (i.e. receiving data). Furthermore, the “receive …” limitation is insignificant extra-solution activity that is well-understood, routine, and conventional according to MPEP 2106.05(d) (“The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity… i. Receiving or transmitting data over a network). Additionally, the “train an artificial intelligence model …” limitation is insignificant extra-solution activity that is well-understood, routine, and conventional according to MPEP 2106.05(d) as shown by Ogale et al. (US 10,013,773 B1) in Col. 18, lines 19-25: “the training system uses conventional machine-learning techniques to train the neural network, such as stochastic gradient descent with backpropagation. For example, the training system can backpropagate gradients of a loss function that is based on the determined error to adjust current values of the parameters of the neural network system to optimize the loss function.” Mere instructions to apply an exception cannot provide an inventive concept. The claim is not patent eligible.
Regarding Claim 19,
Claim 19 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 19 is directed to a computer program product comprising one or more computer readable storage media, which is directed to an article of manufacture, one of the statutory categories.
Step 2A Prong One Analysis: The limitations:
“generate one or more vector functions for each one of a plurality of entities in the knowledge graph”
As drafted, under their broadest reasonable interpretations, cover mental processes (concepts performed in the human mind (including an observation, evaluation, judgement, opinion)) but for the recitation of mere instructions to apply language (See MPEP 2106.05(f)) and insignificant extra-solution activity (See MPEP 2106.05(g)). The above limitations in the context of this claim encompass generating vector functions for each of the entities in the knowledge graph (corresponds to evaluation and judgement; in particular, a human, with the assistance of pen and paper, can generate vector functions for each entity in the knowledge graph).
Step 2A Prong Two Analysis: The judicial exceptions are not integrated into a practical application. In particular, the claim recites additional elements that are mere instructions to apply (See MPEP 2106.05(f)) or insignificant extra-solution activity (See MPEP 2106.05(g)). The recitation of additional elements in claim 15 of a computing system, processor, and a generic AI model, as drafted, are reciting mere instructions to apply language such that it amounts to no more than mere instructions to apply the exceptions. Furthermore, the “receive …” and “train …” limitations of claim 15 are additional elements that correspond to insignificant extra-solution activity as mere data gathering. Therefore, the additional elements do not integrate the abstract ideas into a practical application.
Step 2B Analysis: The claim does 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, all of the additional elements are “mere instructions to apply an exception” (I.e. the additional elements describe computer readable storage media, program instructions, and a generic AI model for applying the abstract ideas) or insignificant extra-solution activity (i.e. receiving data). Furthermore, the “receive …” limitation is insignificant extra-solution activity that is well-understood, routine, and conventional according to MPEP 2106.05(d) (“The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity… i. Receiving or transmitting data over a network). Additionally, the “train an artificial intelligence model …” limitation is insignificant extra-solution activity that is well-understood, routine, and conventional according to MPEP 2106.05(d) as shown by Ogale et al. (US 10,013,773 B1) in Col. 18, lines 19-25: “the training system uses conventional machine-learning techniques to train the neural network, such as stochastic gradient descent with backpropagation. For example, the training system can backpropagate gradients of a loss function that is based on the determined error to adjust current values of the parameters of the neural network system to optimize the loss function.” Mere instructions to apply an exception cannot provide an inventive concept. The claim is not patent eligible.
Regarding Claim 20,
Claim 20 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 20 is directed to a computer program product comprising one or more computer readable storage media, which is directed to an article of manufacture, one of the statutory categories.
Step 2A Prong One Analysis: The limitations:
“generate one or more vector functions representing a relationship between each one of a plurality of entities in the knowledge graph”
As drafted, under their broadest reasonable interpretations, cover mental processes (concepts performed in the human mind (including an observation, evaluation, judgement, opinion)) but for the recitation of mere instructions to apply language (See MPEP 2106.05(f)) and insignificant extra-solution activity (See MPEP 2106.05(g)). The above limitations in the context of this claim encompass generating vector functions representing a relationship between the entities in the knowledge graph (corresponds to evaluation and judgement; in particular, a human, with the assistance of pen and paper, can generate vector functions representing a relationship between each entity in the knowledge graph).
Step 2A Prong Two Analysis: The judicial exceptions are not integrated into a practical application. In particular, the claim recites additional elements that are mere instructions to apply (See MPEP 2106.05(f)) or insignificant extra-solution activity (See MPEP 2106.05(g)). The recitation of additional elements in claim 15 of a computing system, processor, and a generic AI model, as drafted, are reciting mere instructions to apply language such that it amounts to no more than mere instructions to apply the exceptions. Furthermore, the “receive …” and “train …” limitations of claim 15 are additional elements that correspond to insignificant extra-solution activity as mere data gathering. Therefore, the additional elements do not integrate the abstract ideas into a practical application.
Step 2B Analysis: The claim does 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, all of the additional elements are “mere instructions to apply an exception” (I.e. the additional elements describe computer readable storage media, program instructions, and a generic AI model for applying the abstract ideas) or insignificant extra-solution activity (i.e. receiving data). Furthermore, the “receive …” limitation is insignificant extra-solution activity that is well-understood, routine, and conventional according to MPEP 2106.05(d) (“The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity… i. Receiving or transmitting data over a network). Additionally, the “train an artificial intelligence model …” limitation is insignificant extra-solution activity that is well-understood, routine, and conventional according to MPEP 2106.05(d) as shown by Ogale et al. (US 10,013,773 B1) in Col. 18, lines 19-25: “the training system uses conventional machine-learning techniques to train the neural network, such as stochastic gradient descent with backpropagation. For example, the training system can backpropagate gradients of a loss function that is based on the determined error to adjust current values of the parameters of the neural network system to optimize the loss function.” Mere instructions to apply an exception cannot provide an inventive concept. The claim is not patent eligible.
Response to Arguments
Applicant's arguments, filed 12/18/2025, with respect to the 35 U.S.C. 101 abstract idea rejections to the claims have been fully considered but they are not persuasive. Applicant asserts “
In the Office Action, Examiner has rejected pending claims 1, 3-8, 10-15, and 17-20 under 35 U.S.C. § 101 as allegedly, "directed to an abstract idea without significantly more." Applicant respectfully disagrees and provides as follows:
While not conceding to the substance of the rejection, Applicant amends independent claims 1, 8, and 15 (independent claim 1 provided as representative): …
Ab initio, please note that in this Response, Applicant has further amended claims 1, 8, and 15 to clarify that embodiments of Applicant's invention are generally directed to, "providing a continuous knowledge graph in a computing system by a processor to discover new insights from knowledge graphs via utilization of link prediction to detect likely yet previously unknown relationships between entities based upon existing relationship" including the further steps as provided above.
Step 2A - Prong 1
The Office Action indicates that under Step 2A, Prong One, Applicant's claims, "cover mental processes (concepts performed in the human mind (including an observation, evaluation, judgment, opinion)) but for the recitation of mere instructions to apply language...." This is respectfully controverted by Applicant. Very recently, on August 4, 2025, the USPTO has issued a memo entitled, "Reminders on evaluating subject matter eligibility of claims under 35 U.S.C. § 101" (the "AUGUST 4, 2025 MEMO") clarifying the scope of rejections under 35 U.S.C. § 101, particularly in artificial intelligence related applications. The AUGUST 4, 2025 MEMO specifically indicates:
[A] claim does not recite a mental process when it contains limitation(s) that cannot be practically be performed in the human mind, for instance when the human mind is not equipped perform the claim limitation(s).
The mental process grouping is not without limits. Examiners are reminded not to expand this grouping in a manner that encompasses claim limitations that cannot practically be performed in the human mind.... Claim limitations that encompass AI in a way that cannot be practically performed in the human mind do not fall within this grouping [emphasis added].
In a similar fashion to the cited portions of the AUGUST 4, 2025 MEMO, is respectfully submitted that the steps associated with Applicant's claims 1, 8, and 15 cannot practically be performed as "mental processes." Applicant's claims, for example, recite (inter alia): …
It is respectfully controverted by Applicant, therefore, that a "mental process[]" is at stake. The AUGUST 4, 2025 MEMO supports this view. The plain language of the claim elements as provided above, as well as others provided herein support Applicant's view that humans with "pencil and paper" cannot perform these steps.
Further supporting the view that Applicant's embodiments are patentable subject-matter under 35 U.S.C. § 101, in the 2019 Revised Patent Subject Matter Eligibility Guidance ("2019 PEG"), the USPTO has offered Example 39 as specifically indicating that a "Method for Training a Neural Network for Facial Detection" is patent eligible. See 2019 PEG at Example 39. …
In a similar manner to Example 39, Applicant's claims 1, 8, and 15 are not performed "practically in the human mind." Generally, Example 39 is generally directed towards training and utilization of an artificial intelligence model for a real-world function, and is similar to Applicant's claims 1, 8, and 15. Applicant's claims 1, 8, and 15 recite, "receiving heterogeneous data regarding a knowledge graph, the knowledge graph having a plurality of entities and one or more edges, the edges representing relationships between the plurality of entities in the knowledge graph; training an artificial intelligence model utilizing the heterogenous data, training the artificial intelligence model involving optimizing a loss function while tuning hyperparameters; predicting using the trained artificial intelligence model one or more weighted values of an edge between a pair of entities in a knowledge graph based on one or more candidate statements, each edge associated with a label signifying a particular relationship represented by the edge; ..." Because of the similarity to Example 39, it is also respectfully submitted to Examiner that Applicant's pending claims 1, 8, and 15 are patentable subject-matter, pursuant to 35 U.S.C. § 101.
Step 2A -Prong 2
The Office Action also indicates that under Step 2A, Prong Two, Applicant's claims, "[t]he judicial exceptions are not integrated into a practical application." This is also respectfully controverted by Applicant. MPEP 2106.04(d) supports the view that under Step 2A, Prong Two, pending claims indicate a "practical application" is present. MPEP 2106.04(d) indicates that a "relevant consideration[] for evaluating whether additional elements integrate a judicial exception into a practical application" is whether embodiments are related to, "an improvement in the functioning of a computer, or an improvement to other technology or technical field. .. ." Applicant currently amends claims 1, 8, and 15, to indicate these embodiments are directed towards the "practical application" of "providing a continuous knowledge graph in a computing system by a processor to discover new insights from knowledge graphs via utilization of link prediction to detect likely yet previously unknown relationships between entities based upon existing relationships; .. ." and then using the "trained artificial intelligence model" to perform certain functions in order to, "defin[e] the one or more weighted values to represent a predicted, unknown relationship between the pair of entities in the knowledge graph based on existing weighted relationships between one or more of [[the]] a plurality of entities in the knowledge graph and the predicted weighted values." Further details regarding the "practical application" are contained in Applicant's embodiments discussed herein.
Applicant's Specification filed November 29, 2021 discusses the problem embodiments of the invention confront, specifically how to confront the deluge of data faced from the internet (i.e., a problem faced in computer technology). Para. [0002] indicates: …
Embodiments of the invention offer a solution to handling the large amounts of data presented in the internet via utilization of knowledge graphs: embodiments offer improvements in these knowledge graphs, as discussed in Applicant's claims. …
Embodiments of the invention, as discussed above, more specifically utilize computer technology and artificial intelligence to improve knowledge graphs, for the purposes discussed.
For these reasons, it is respectfully submitted that a "practical application" is present, pursuant to MPEP 2106.04(d).
Step 2B
Finally, under Step 2B, it is respectfully submitted that in any event, Applicant's claims, "recite additional elements that are sufficient to amount to significantly more than the judicial exception." MPEP 2016.05 clarifies that this is directed towards a "search for an inventive concept." Applicant's "inventive concept" is, as restated in Applicant's claims 1, 8, and 15 is (at least-in part) is generally to, "defin[e] the one or more weighted values to represent a predicted, unknown relationship between the pair of entities in the knowledge graph based on existing weighted relationships between one or more of [[the]] a plurality of entities in the knowledge graph and the predicted weighted values."
Applicant's Specification supports this view. By non-limiting example, further discussion of the "inventive concept" is provided in Paras. [0017], [0020], [0022], [00101], [00102],... etc. as reproduced below: Para. [0022] is particularly instructive. …
Summary with Regard to Rejections Under 35 U.S.C. § 101
For these reasons, it is respectfully submitted to Examiner that Applicant's claims 1, 8, and 15 and all claims depending upon these qualify as patentable subject-matter under 35 U.S.C. § 101 and these rejections should be withdrawn.” (Remarks Pages 8-17).
Examiner’s Response:
The examiner respectfully disagrees. Applicant has made general assertions that claim 1 recites claim elements that are not directed to an abstract idea and that even if the claim elements are directed to an abstract idea, the judicial exceptions are integrated into a practical application because the claims recite elements that cannot reasonably be characterized as covering mental processes or reflect an improvement to a technology or technical field. Regarding the “discover new insights from knowledge graphs via utilization of link prediction to detect likely yet previously unknown relationships between entities based upon existing relationships” limitation of claim 1, this limitation, under its broadest reasonable interpretation, encompasses discovering new insights from a knowledge graph using link prediction to detect new relationships between entities based on existing relationships (corresponds to evaluation and judgement; in particular, a human, with the assistance of pen and paper, can use existing relationships between entities of a knowledge graph to detect new relationships between entities to discover new insights from the knowledge graph). Furthermore, regarding the “defining the one or more weighted values to represent a predicted, unknown relationship between the pair of entities in the knowledge graph based on existing weighted relationships between one or more of a plurality of entities in the knowledge graph and the predicted weights values” limitation of claim 1, this limitation, under its broadest reasonable interpretation is considered an abstract idea that encompasses defining the weighted values to represent a predicted, unknown relationship between the entities pair based on existing weighted relationships and the predicted weighted values between entities in the knowledge graph (corresponds to evaluation and judgement; in particular, a human, with the assistance of pen and paper, can use existing weighted relationships between entities in the knowledge graph and the predicted weighted values to define the weighted values to represent a predicted, unknown relationship between the pair of entities). Moreover, since these limitations are directed to a judicial exception, they cannot provide any alleged solution or improvement. See MPEP 2106.05(a): “It is important to note, the judicial exception alone cannot provide the improvement. The improvement can be provided by one or more additional elements. See the discussion of Diamond v. Diehr, 450 U.S. 175, 187 and 191-92, 209 USPQ 1, 10 (1981)) in subsection II, below.”
Additionally, regarding the "predicting using the trained artificial intelligence model one or more weighted values of an edge between a pair of entities in a knowledge graph based on one or more candidate statements, each edge associated with a label signifying a particular relationship represented by the edge" and "generating using the trained artificial intelligence model a confidence score for the one or more predicted weighted values" limitations of claim 1, these limitations, under their broadest reasonable interpretations, correspond to evaluation and judgement with the assistance of pen and paper (the "predicting ... one or more weighted values of an edge between a pair of entities in a knowledge graph based on one or more candidate statements, each edge associated with a label signifying a particular relationship represented by the edge" limitation is a mental process performable by the human mind; a human, with the assistance of pen and paper, can use candidate statements to predict weighted values of an edge between entities of a knowledge graph; and the limitation "generating ... a confidence score for the one or more predicted weighted values" is a mental process performable by the human mind; a human, with the assistance of pen and paper, can generate a confidence score for the predicted weighted values) and mere instructions to apply language using a generic computer (the "using the trained artificial intelligence model" limitations are mere instructions to apply language for the abstract ideas predicting weighted values and generating a confidence score). The "using the trained artificial intelligence model" limitations are a high level recitation of applying an AI model to previously determined data such that it amounts to no more than merely using a computer as a tool to perform generic computer functions. As such, the recitation that the predicting and generating procedures are to be performed with such a model is a mere instruction to apply the judicial exception using a generic computer programmed with a generically recited class of computer algorithm. See MPEP § 2106.05(f): “Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer. … Thus, for example, claims that amount to nothing more than an instruction to apply the abstract idea using a generic computer do not render an abstract idea eligible.” Furthermore. since the “predicting …” and “generating …” limitations are directed to a judicial exception, they cannot provide any alleged solution or improvement. See MPEP 2106.05(a): “It is important to note, the judicial exception alone cannot provide the improvement. The improvement can be provided by one or more additional elements. See the discussion of Diamond v. Diehr, 450 U.S. 175, 187 and 191-92, 209 USPQ 1, 10 (1981)) in subsection II, below.”
Thus, it is the additional elements that are analyzed to determine whether the judicial exception is integrated into a practical application, not the judicial exception itself. Regarding the additional elements in claim 1 of “a computing system”, “a processor”, and “using the trained artificial intelligence model”, as drafted, under their broadest reasonable interpretations, are high level recitations of applying a computing system, processor, and a generic AI model to implement the abstract ideas such that it amounts to no more than merely using a computer as a tool to perform generic computer functions. As such, the recitation that the abstract ideas are to be performed with such circuitry is a mere instruction to apply the judicial exception using a generic computer component. See MPEP 2106.05(f). “Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer. … Thus, for example, claims that amount to nothing more than an instruction to apply the abstract idea using a generic computer do not render an abstract idea eligible.” Furthermore, regarding the additional element in claim 1 of “training an artificial intelligence model utilizing the heterogeneous data, training the artificial intelligence model involving optimizing a loss function while tuning hyperparameters”, under its broadest reasonable interpretation, is an additional element that corresponds to insignificant extra-solution activity that is well-understood, routine, and conventional according to MPEP 2106.05(d) as shown by Ogale et al. (US 10,013,773 B1) in Col. 18, lines 19-25: “the training system uses conventional machine-learning techniques to train the neural network, such as stochastic gradient descent with backpropagation. For example, the training system can backpropagate gradients of a loss function that is based on the determined error to adjust current values of the parameters of the neural network system to optimize the loss function.” Furthermore, the additional element in claim 1 of “receiving heterogeneous data regarding a knowledge graph, the knowledge graph having a plurality of entities and one or more edges, the edges representing relationships between the plurality of entities in the knowledge graph”, as drafted, amounts to insignificant extra-solution activity. In particular, the additional element corresponds to mere data gathering. See MPEP 2106.05(g). Accordingly, the additional elements do not integrate the abstract ideas into a practical application.
Furthermore, the claim does 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, all of the additional elements are “mere instructions to apply an exception” (I.e. the additional elements describe a computing system, processor, and a generic AI model for applying the abstract ideas) or insignificant extra-solution activity (i.e. receiving data). Furthermore, the “receiving …” limitation is insignificant extra-solution activity that is well-understood, routine, and conventional according to MPEP 2106.05(d) (“The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity… i. Receiving or transmitting data over a network). Additionally, the “training an artificial intelligence model …” limitation is insignificant extra-solution activity that is well-understood, routine, and conventional according to MPEP 2106.05(d) as shown by Ogale et al. (US 10,013,773 B1) in Col. 18, lines 19-25: “the training system uses conventional machine-learning techniques to train the neural network, such as stochastic gradient descent with backpropagation. For example, the training system can backpropagate gradients of a loss function that is based on the determined error to adjust current values of the parameters of the neural network system to optimize the loss function.” Mere instructions to apply an exception cannot provide an inventive concept. The claim is not patent eligible.
With regards to Applicant's arguments regarding Example 39 of the 2019 PEG, Example 39 is eligible under 35 U.S.C. 101 as the claim does not recite a judicial exception under Step 2A - Prong 1. However, as discussed above, claim 1 of the instant application recites the limitations “discover new insights from knowledge graphs via utilization of link prediction to detect likely yet previously unknown relationships between entities based upon existing relationships”, "predicting … one or more weighted values of an edge between a pair of entities in a knowledge graph based on one or more candidate statements, each edge associated with a label signifying a particular relationship represented by the edge”, “generating … a confidence score for the one or more predicted weighted values”, and “defining the one or more weighted values to represent a predicted, unknown relationship between the pair of entities in the knowledge graph based on existing weighted relationships between one or more of a plurality of entities in the knowledge graph and the predicted weights values" which, under their broadest reasonable interpretations, correspond to mental processes performable by the human mind. Therefore claim 1 of the instant application is different from Example 39 of the 2019 PEG in that claim 1 does recite a judicial exception under Step 2A - Prong 1.
In other words, the limitations of “discover new insights from knowledge graphs via utilization of link prediction to detect likely yet previously unknown relationships between entities based upon existing relationships”, "predicting … one or more weighted values of an edge between a pair of entities in a knowledge graph based on one or more candidate statements, each edge associated with a label signifying a particular relationship represented by the edge”, “generating … a confidence score for the one or more predicted weighted values”, and “defining the one or more weighted values to represent a predicted, unknown relationship between the pair of entities in the knowledge graph based on existing weighted relationships between one or more of a plurality of entities in the knowledge graph and the predicted weights values” are abstract ideas that are directed to a judicial exception, so they cannot provide any alleged solution or improvement. Additionally, the limitations of “receiving heterogeneous data regarding a knowledge graph, the knowledge graph having a plurality of entities and one or more edges, the edges representing relationships between the plurality of entities in the knowledge graph” and “training an artificial intelligence model utilizing the heterogenous data, training the artificial intelligence model involving optimizing a loss function while tuning hyperparameters” are additional elements corresponding to insignificant extra-solution activity that is well-understood, routine, and conventional. Furthermore, the other additional elements recited in claim 1 are directed to mere instructions to apply an abstract idea. Therefore, claim 1 does not recite additional element(s) that can provide any alleged solution, improvement, or inventive concept.
Applicant relies on the arguments above regarding independent claims 8 and 15 and dependent claims 3-7, 10-14, and 17-20, therefore the response above is applicable to those claims.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to BRIAN J HALES whose telephone number is (571)272-0878. The examiner can normally be reached M-F 9:00am - 5:00pm.
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/BRIAN J HALES/Examiner, Art Unit 2125
/KAMRAN AFSHAR/Supervisory Patent Examiner, Art Unit 2125