DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This Office action is in response to the amendments, arguments and remarks, filed on 1/20/2026, in which claim(s) 12-25 is/are presented for further examination.
Claim(s) 12, 21 and 22 has/have been amended.
Claim(s) 1-11 has/have been previously cancelled.
Response to Amendment
Applicant’s amendment(s) to claim(s) 12, 21 and 22 has/have been accepted.
The examiner thanks applicant’s representative for pointing out where s/he believes there is support for the amendment(s).
Response to Arguments
Applicant’s arguments with respect to claim(s) 12-25, filed on 1/20/2026, have been fully considered but they are not persuasive. Accordingly, this action has been made FINAL.
Applicant argues that claim(s) 12-25 are patent eligible, see the middle of page 6 to page 14 of applicant’s remarks, filed on 1/20/2026.
The examiner respectfully disagrees. Please see the updated 35 U.S.C. 101 rejections in light of applicant’s amended claims below. Using the BRI, the claims can be interpreted as an abstract idea without significantly more. Using the BRI (and in a simplified example covered by the claims), the steps currently recited can be interpreted as mere mental steps performed in the mind with the aid of pen and paper, which are merely implemented using a computer, which is not patent eligible. The current claims merely recite extending a knowledge graph, which can be simply drawn on paper, as a series of nodes with lines connecting the nodes indicating the relationships between the nodes, see the picture below.
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Example of a knowledge graph
Using the BRI, the claims recite updating the knowledge graph based on certain constraints (e.g., in the knowledge graph above “James is not a place”), which can all be evaluated/performed in the human mind. If extending the knowledge graph is claimed in a way that it can only be performed in a computer (e.g., some examples of activities that can only be performed in a computer include accessing computer memory/storage, writing to computer memory/storage, determining the percentage of a processor’s capacity being used, determining the percentage of memory used …) and is somehow used by the computer to obtain a practical application/result (e.g., some examples of using the extended knowledge graph by a computer for a practical application result include using the updated/extended knowledge graph
) then perhaps the claims could be patent eligible; however, as currently presented the claims are not patent eligible.
Regarding applicant’s argument:
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See the bottom of page 9 to the top of page 10 of applicant’s remarks, filed on 1/20/2026.
The examiner respectfully disagrees. The Desjardins case deals with training machine learning, the present application can be differentiated because the (present) claims in the instant application recite nothing about training machine learning nor does the instant applicant have anything to do with training machine learning. Thus, the Desjardins ruling does not apply to the instant application and is unpersuasive regarding the 35 U.S.C. 101 rejections for the instant application.
Note: The examiner is not saying that the invention cannot be patent eligible, but, as presently claimed, the invention is not patent eligible.
Applicant’s arguments with respect to the rejection(s) of claim(s) 12-25, under 35 U.S.C. 103, see page 15-17 of applicant’s remarks, filed on 1/20/2026, have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
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.
Claim(s) 12-25 is/are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claim 12 recites “A computer-implemented method for extending a knowledge graph …”; the claim recites a series of steps and, therefore, is a process. Claim 21 recites “A device for extending a knowledge graph …”; and, therefore, is a machine. Claim 22 recites “A non-transitory computer-readable medium … for extending a knowledge graph …” and, therefore, is a manufacture.
Claim(s) 12, 21 and 22 recite(s) the limitation(s) of:
“predefining an input variable including an instance to be extended and a relation associated with the instance to be extended and/or an attribute of the knowledge graph related to the instance to be extended;” (mental process)
“determining a first property assertion constraint associated with the input variable;” (mental process)
“determining a query fragment for the first property assertion constraint;” (mental process)
“determining a query including a predefined core query and the query fragment;” (mental process)
“executing the query on the knowledge graph, a first result being determined that includes either: (i) at least one permissible instance and/or at least one permissible literal for extending the knowledge graph, or (ii) no instance and no literal, such that the knowledge graph can only be extended in an error-avoiding manner by an extension that includes the at least one permissible instance and/or the at least one permissible literal, wherein an error check of the knowledge graph after the knowledge graph is extended is avoided;” (mental process with the aid of pen and paper)
The limitation(s), as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind, see above. That is, nothing in the claim precludes the step from practically being performed in the mind. The mere nominal recitation of: “a knowledge graph” in claim(s) 12, 21 and 22, “a device” in claim(s) 21 and “a non-transitory computer-readable medium” and “a computer” in claim(s) 22 and do(es) not take the claim limitation(s) out of the mental processes grouping. Thus, the claim(s) recite(s) a mental process. The claim(s) is/are directed to an abstract idea.
This judicial exception is not integrated into a practical application because the claims amount to no more than mere instructions to implement the abstract idea on a general purpose computer. The claim(s) is/are directed to an abstract idea.
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because, as explained below, the recitation(s) of the a device, a non-transitory computer-readable medium and a computer amount(s) to nothing more than applying the exception with a generic, off-the-shelf component. The background does not provide any indication that the components are anything other than a generic, off-the-shelf display component. Accordingly, a conclusion that the receiving, transmitting and executing steps are a well-understood, routine and conventional activity is supported.
Regarding claim(s) 14, 15, 16, 17, 18, 19, 23, 24 and 25, the claim(s) recite(s) the limitation(s) of “wherein a second property assertion constraint is determined, a second result being determined for the second property assertion constraint that either includes: (i) at least one permissible instance and/or at least one permissible literal for extending the knowledge graph, or (ii) no instance and no literal, a sequence of inputs of the user or inputs from the machine being requested depending on the first result and the second result, and the knowledge graph is extended depending on the sequence, the sequence defining an order for queries of the inputs in which a first query is made according to the first result before a second query is made according to the second result, the second result or the second query being determined depending on an input in response to the first query;” (mental process with the aid of pen and paper) in claim 14, “the knowledge graph is extended by a predefined relation of the instance to be extended to the at least one permissible instance, and/or a selection of at least one permissible literal for extending the knowledge graph is detected, and the knowledge graph is extended by an attribute for the instance to be extended;” (mental process with the aid of pen and paper) in claim 15, “determining the first property assertion constraint associated with the instance to be extended or associated with a class associated with the instance to be extended;” (mental process) in claim 16, “determining the first property assertion constraint associated with a second class that is closest to the first class in a class hierarchy;” in claim 17, “wherein the determining of the first property assertion constraint includes finding a constraint of the graph that applies to the instance;” (mental process) in claim 18, “the query is determined without a query fragment;” (mental process) in claim 19, “prior to extending the knowledge graph, checking the extension for error;” (mental process) in claims 23-25, the limitation(s), as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. The claim(s) is/are not patent eligible.
Regarding claim(s) 13, 15, 19 and 20, the claim(s) recite(s) the limitation(s) of “further comprising displaying the first result displayed to a user or outputting the first result to a machine;” (transmitting data) in claim 13, “wherein a selection of at least one permissible instance for extending the knowledge graph is detected;” (data gathering) in claim 15, “wherein when it is detected that no relevant property assertion constraint exists;” (data gathering) in claim 19, “wherein the input variable is read from a graph database in which the knowledge graph is stored including a memory for triples of the knowledge graph, the query being executed on the graph database;” (data gathering) in claim 20, amounts to nothing more than applying the exception with a generic, off-the-shelf computer components. The steps are considered to be insignificant extra-solution activity. The background does not provide any indication that the computing device is anything other than a generic, off-the-shelf computer component. Accordingly, a conclusion that the steps are a well-understood, routine and conventional activity is supported.
Even when considered in combination, these additional elements represent mere instructions to apply an exception with well understood, routine and conventional insignificant extra-solution activity, which does not provide significantly more to the abstract idea. The claim(s) is/are not patent eligible.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 12-25 is/are rejected under 35 U.S.C. 103 as being unpatentable over Gong et al., CN 110147376 A (hereinafter “Gong”; Note: Mapping is based on the English translation attached/provided) in view of Bucuvalas, US 2007/0266366 A1 (hereinafter “Bucuvalas”) in further view of Hogan et al., “Knowledge Graphs”, ACM Digital Library, https://dl.acm.org/doi/10.1145/3447772 published on July 2, 2021 (hereinafter “Hogan”).
Claims 12, 21 and 22
Gong discloses a computer-implemented method for extending a knowledge graph, comprising the following steps:
predefining an input variable including an instance to be extended and a relation associated with the instance to be extended (Gong, page 3, Summary of the invention, 6th paragraph, see changing the data structure of the model, completely describing the concepts and terms and the relationship between the two, comprises five elements: class (C), a relationship (R), attribute (At), axioms (Rel) and instance (Ao), in addition to a general meaning of the concept; Gong, page 5, Summary of the invention, 7th paragraph, see dynamic extension; and Gong, page 5, Summary of the invention, 8th paragraph, see binding extension) and/or an attribute of the knowledge graph related to the instance to be extended);
determining a first property assertion constraint associated with the input variable (Gong, page 2, Background, 2nd paragraph, see inquiring of the specified predicate value [i.e., where the parameter for the specified value of the predicate is being interpreted as the “input variable”);
determining a query fragment for the first property assertion constraint (Gong, page 2, Background, 2nd paragraph, see inquiring of the specified predicate value [i.e., where a query predicate is part of a query, which is being interpreted as the “query fragment”]);
determining a query including a predefined core query and the query fragment (Gong, page 2, Background, 2nd paragraph, see inquiring of the specified predicate value, execution efficiency, search time and retrieval of information; and Gong, page 5, Summary of the Invention, 3rd paragraph, see compound query, query result needs to satisfy all of the query condition [i.e., where “compound” means multiple parts to the query including a core part and other parts, which are interpreted as the “query fragments”] and the query result needs to satisfy all of the query conditions); and
executing the query on the knowledge graph (Gong, page 4, Summary of the invention, 11th paragraph, see searching the expression according to the retrieval request and object matching the query; Gong, page 5, Summary of the invention, 2nd paragraph, see the triple index can be matched to search and query using a relation, in the specified triplets w, p, o> if it needs to search the relationship between S and O; and Gong, page 6, Summary of the invention, 2nd paragraph, see the triple automatic processing RDF [i.e., knowledge graph] can conveniently describe the mutual relationship between the object and its attribute, the machine program can freely exchange data on the network, to realize network resource. RDF data in each basic structure is a subject resource to the corresponding relation and resource object to triple rmittel w, p, o> data structure to represent the RDF data. wherein, t represents RDF triple, i.e., I represents a uniform resource identifier (URL), B represents the empty node, L represents a word node. RDF triple associated with one or more of the RDF can be composed of directed graph, RDF with a directed graph composed of nodes and edges of the marked, describing the subject, object and the corresponding relationship of the attribute. …”), a first result being determined that includes either: (i) at least one permissible instance (Gong, page 4, Summary of the invention, 11th paragraph, see searching the expression according to the retrieval request and object matching the query; and Gong, page 5, Summary of the Invention, 3rd paragraph, see compound query, query result needs to satisfy all of the query condition) and/or
Gong does not appear to explicitly disclose at least one permissible literal for extending the knowledge graph, or (ii) no instance and no literal, such that the knowledge graph can only be extended in an error-avoiding manner by an extension that includes the at least one permissible instance and/or the at least one permissible literal, wherein an error check of the knowledge graph after the knowledge graph is extended is avoided.
Bucuvalas discloses at least one permissible literal for extending the knowledge graph (Bucuvalas, [7265], see, by composition, one means: given two DAGs, adding an arc between the exit node in one graph to an entry node in the other graph produces a “composed” graph [i.e., adding the arc in the directed acyclic graph/DAG is being interpreted as “extending the knowledge graph”]. This composed graph is always a DAG; and Bucuvalas, [7271], see both graphs are DAGs so there cannot be a loop “internal” to either. Otherwise, it would contradict the premise that they are both DAGs. In addition, the added arcs between the graphs are unidirectional [i.e., adding the arc in the directed acyclic graph/DAG is being interpreted as “extending the knowledge graph”], so there cannot be a loop between the graphs. Thus the existence of a loop is inconsistent with the assumptions), or (ii) no instance and no literal, such that the knowledge graph can only be extended in an error-avoiding manner by an extension that includes the at least one permissible instance (Bucuvalas, [7067], see the process described herein is used to design and verify that a language, regardless of its form, both is compatible with FIOSM generation, and that the necessary algorithms exist for successful error-free generation; and Bucuvalas, [7929]-[7930], see, to do this, Pat specifies that Product in the cases she is concerned with is “c30”, and then specifies that the LoanAmount must be less than or equal to $417K. FIG. 2 shows how Pat does this in the ioRules interface. Pat then asks the ioRules system to evaluate the constraint, by clicking the “Validate Policy” button. The system creates a model for the constraint, and determines whether or not the model of her program is subsumed by the model for the constraint, that is, whether the logic of her program implies that the constraint is always satisfied. In this case, the answer is yes. On further reflection, Pat realizes that not just a c30 loan, but any conventional loan, should satisfy the same constraint on loan amount. Pat therefore modifies her policy to include c15 as well as c30, as shown in FIG. 235. Now when Pat asks for the new policy to be validated, the system indicates that it is NOT satisfied [i.e., an “impermissible instance” was found]. Pat knows that she has an error to correct. Now Pat can use the ioRules interface to learn WHY the error is occurring. Pat hits the trace button at the bottom of FIG. 235, and opens the window in FIG. 236. This window indicates that the eligibility table specifies a loan limit for c15 of 418K, clearly a mistake. Pat corrects this error and moves to her next task, where this shows an example of error checking constraints to provide an “error-avoiding manner by an extension”) and/or the at least one permissible literal (Bucuvalas, [6885], see a data value may be expressed as a literal value (i.e. a member of the permissible set) or as a result of an operation on other data).
Gong and Bucuvalas are analogous art because they are from the same field of endeavor such as graphs.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention, having the teachings of Gong and Bucuvalas before him/her, to modify the graph of Gong to include the permissible literals of Bucuvalas because it allow additional methods to define edge relationships.
The suggestion/motivation for doing so would have been to more completely, efficiently and accurately verify proper operation of a new piece of software, see Bucuvalas, [6840].
Therefore, it would have been obvious to combine Bucuvalas with Gong to obtain the invention as specified in the instant claim(s).
The combination of Gong and Bucuvalas does not appear to explicitly disclose wherein an error check of the knowledge graph after the knowledge graph is extended is avoided.
Hogan discloses wherein an error check of the knowledge graph after the knowledge graph is extended is avoided (Hogan, 71:9, 2.3 Validation, see validating that the data graph follows a particular structure that is “complete”; Hogan, 71:9, 2.3.1 Shape Graphs, see nodes conform to a shape if an only if they satisfy all constraints defined on the shape; and Hogan, 71:10, 2.3.2 Conformance, see that a shape satisfies all of the constraints and that a graph is valid if and only if every node that each shape targets conforms to that shape, where checking for a structure being complete and that the structure satisfies all constraints corresponds to checking that the data graph is complete, correct and consistent, per [0047] of applicant’s spec., which, in turn, avoids error checking of the knowledge graph after the knowledge graph is extended).
Gong, Bucuvalas and Hogan are analogous art because they are from the same field of endeavor such as graphs.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention, having the teachings of Gong, Bucuvalas and Hogan before him/her, to modify the graph with permissible literals of the combination of Gong and Bucuvalas to include the validation of Hogan because it allow knowledge graphs to be constructed properly.
The suggestion/motivation for doing so would have been to integrate, manage and extract value from diverse sources of data at large scale, see Hogan, 71:2, 1 Introduction.
Therefore, it would have been obvious to combine Hogan with the combination of Gong and Bucuvalas to obtain the invention as specified in the instant claim(s).
Claim(s) 21 and 22 recite(s) similar limitations to claim 12 and is/are rejected under the same rationale.
With respect to claim 21, Gong discloses a device for extending a knowledge graph (Gong, Summary of the Invention, page 9, 2nd paragraph, see database, which requires a processor to run).
With respect to claim 22, Gong discloses a non-transitory computer-readable medium on which is stored a computer program including computer-readable instructions for extending a knowledge graph (Gong, Summary of the Invention, page 9, 2nd paragraph, see memory).
Claim 13
With respect to claim 13, the combination of Gong, Bucuvalas and Hogan discloses further comprising displaying the first result displayed to a user or outputting the first result to a machine (Gong, page 4, Summary of the invention, 11th paragraph, see searching the expression according to the retrieval request and object matching the query).
Claim 14
With respect to claim 14, the combination of Gong, Bucuvalas and Hogan discloses wherein a second property assertion constraint is determined, a second result being determined for the second property assertion constraint that either includes: (i) at least one permissible instance and/or at least one permissible literal for extending the knowledge graph (Gong, page 4, Summary of the invention, 11th paragraph, see searching the expression according to the retrieval request and object matching the query; Gong, page 5, Summary of the invention, 2nd paragraph, see the triple index can be matched to search and query using a relation, in the specified triplets w, p, o> if it needs to search the relationship between S and O, where the second of the specified triplets is being interpreted as the “second property assertion constraint”; and Gong, page 6, Summary of the invention, 2nd paragraph, see the triple automatic processing RDF [i.e., knowledge graph] can conveniently describe the mutual relationship between the object and its attribute, the machine program can freely exchange data on the network, to realize network resource. RDF data in each basic structure is a subject resource to the corresponding relation and resource object to triple rmittel w, p, o> data structure to represent the RDF data. wherein, t represents RDF triple, i.e., I represents a uniform resource identifier (URL), B represents the empty node, L represents a word node. RDF triple associated with one or more of the RDF can be composed of directed graph, RDF with a directed graph composed of nodes and edges of the marked, describing the subject, object and the corresponding relationship of the attribute. …”), or (ii) no instance and no literal, a sequence of inputs of the user or inputs from the machine being requested depending on the first result and the second result, and the knowledge graph is extended depending on the sequence, the sequence defining an order for queries of the inputs in which a first query is made according to the first result before a second query is made according to the second result, the second result or the second query being determined depending on an input in response to the first query.
Claim 15
With respect to claim 15, the combination of Gong, Bucuvalas and Hogan discloses wherein a selection of at least one permissible instance for extending the knowledge graph is detected, and the knowledge graph is extended by a predefined relation of the instance to be extended to the at least one permissible instance, and/or a selection of at least one permissible literal for extending the knowledge graph is detected, and the knowledge graph is extended by an attribute for the instance to be extended (Gong, page 3, Summary of the invention, 6th paragraph, see changing the data structure of the model, completely describing the concepts and terms and the relationship between the two, comprises five elements: class (C), a relationship (R), attribute (At), axioms (Rel) and instance (Ao), in addition to a general meaning of the concept; Gong, page 5, Summary of the invention, 7th paragraph, see dynamic extension; and Gong, page 5, Summary of the invention, 8th paragraph, see binding extension).
Claim 16
With respect to claim 16, the combination of Gong, Bucuvalas and Hogan discloses wherein the determining of the first property assertion constraint includes:
determining the first property assertion constraint associated with the instance to be extended or associated with a class associated with the instance to be extended (Gong, page 2, Background, 2nd paragraph, see inquiring of the specified predicate value [i.e., where the parameter for the specified value of the predicate is being interpreted as the “input variable”; and Gong, page 3, Summary of the invention, 6th paragraph, see changing the data structure of the model, completely describing the concepts and terms and the relationship between the two, comprises five elements: class (C), a relationship (R), attribute (At), axioms (Rel) and instance (Ao), in addition to a general meaning of the concept).
Claim 17
With respect to claim 17, the combination of Gong, Bucuvalas and Hogan discloses wherein the instance to be extended is associated with a first class, and the determining of the first property assertion constraint includes:
determining the first property assertion constraint associated with a second class that is closest to the first class in a class hierarchy (Gong, page 3, Summary of the invention, 6th paragraph, see changing the data structure of the model, completely describing the concepts and terms and the relationship between the two, comprises five elements: class (C), a relationship (R), attribute (At), axioms (Rel) and instance (Ao), in addition to a general meaning of the concept, also can be the RDF triple in the task, and event action name represented as subject resource and object resource, e.g., "oil and gas exploration development" is a class, using triple form (represented as oil and gas exploration and development, rdfs type, Owl: class), relation is a mapping method defined in the main concepts and attributes, mainly refers to the constraint relation of the two, wherein the definition domain is comprised of concept in the concept set, and value field can be composed of concept and value data types; the main relationship between the field main body comprises a child relationship (subClassOf), between the example and the main term of relation (edf); attribute is described mainly characteristic of field in main body concept, it mainly comprises two attributes, namely the data attribute and object attribute and data attribute refers to object associated with the data type value, object attribute refers to object are associated with each other; axioms is description of the eternal truth, it is true under any condition).
Claim 18
With respect to claim 18, the combination of Gong, Bucuvalas and Hogan discloses wherein the determining of the first property assertion constraint includes finding a constraint of the graph that applies to the instance (Gong, page 3, Summary of the invention, 6th paragraph, see changing the data structure of the model, completely describing the concepts and terms and the relationship between the two, comprises five elements: class (C), a relationship (R), attribute (At), axioms (Rel) and instance (Ao), in addition to a general meaning of the concept, also can be the RDF triple in the task, and event action name represented as subject resource and object resource, e.g., "oil and gas exploration development" is a class, using triple form (represented as oil and gas exploration and development, rdfs type, Owl: class), relation is a mapping method defined in the main concepts and attributes, mainly refers to the constraint relation of the two, wherein the definition domain is comprised of concept in the concept set, and value field can be composed of concept and value data types; the main relationship between the field main body comprises a child relationship (subClassOf), between the example and the main term of relation (edf); attribute is described mainly characteristic of field in main body concept, it mainly comprises two attributes, namely the data attribute and object attribute and data attribute refers to object associated with the data type value, object attribute refers to object are associated with each other; axioms is description of the eternal truth, it is true under any condition; and Gong, page 6, Summary of the invention, 2nd paragraph, see the triple automatic processing RDF [i.e., knowledge graph] can conveniently describe the mutual relationship between the object and its attribute, the machine program can freely exchange data on the network, to realize network resource. RDF data in each basic structure is a subject resource to the corresponding relation and resource object to triple rmittel w, p, o> data structure to represent the RDF data. wherein, t represents RDF triple, i.e., I represents a uniform resource identifier (URL), B represents the empty node, L represents a word node. RDF triple associated with one or more of the RDF can be composed of directed graph, RDF with a directed graph composed of nodes and edges of the marked, describing the subject, object and the corresponding relationship of the attribute. …”).
Claim 19
With respect to claim 19, the combination of Gong, Bucuvalas and Hogan discloses wherein when it is detected that no relevant property assertion constraint exists, the query is determined without a query fragment (Gong, page 4, Summary of the invention, 11th paragraph, see searching the expression according to the retrieval request and object matching the query).
Claim 20
With respect to claim 20, the combination of Gong, Bucuvalas and Hogan discloses wherein the input variable is read from a graph database in which the knowledge graph is stored including a memory for triples of the knowledge graph, the query being executed on the graph database (Gong, page 5, Summary of the invention, 2nd paragraph, see the triple index can be matched to search and query using a relation, in the specified triplets w, p, o> if it needs to search the relationship between S and O).
Claims 23-25
With respect to claims 23-25, the combination of Gong, Bucuvalas and Hogan discloses further comprising:
prior to extending the knowledge graph, checking the extension for error (Bucuvalas, [7067], see the process described herein is used to design and verify that a language, regardless of its form, both is compatible with FIOSM generation, and that the necessary algorithms exist for successful error-free generation; and Bucuvalas, [7929]-[7930], see, to do this, Pat specifies that Product in the cases she is concerned with is “c30”, and then specifies that the LoanAmount must be less than or equal to $417K. FIG. 2 shows how Pat does this in the ioRules interface. Pat then asks the ioRules system to evaluate the constraint, by clicking the “Validate Policy” button. The system creates a model for the constraint, and determines whether or not the model of her program is subsumed by the model for the constraint, that is, whether the logic of her program implies that the constraint is always satisfied. In this case, the answer is yes. On further reflection, Pat realizes that not just a c30 loan, but any conventional loan, should satisfy the same constraint on loan amount. Pat therefore modifies her policy to include c15 as well as c30, as shown in FIG. 235. Now when Pat asks for the new policy to be validated, the system indicates that it is NOT satisfied [i.e., an “impermissible instance” was found]. Pat knows that she has an error to correct. Now Pat can use the ioRules interface to learn WHY the error is occurring. Pat hits the trace button at the bottom of FIG. 235, and opens the window in FIG. 236. This window indicates that the eligibility table specifies a loan limit for c15 of 418K, clearly a mistake. Pat corrects this error and moves to her next task, where this shows an example of error checking constraints).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
– Zhang et al., CN 113157939 for information processing; and
– Henrik Dibowski, “Property Assertion Constraints for an Informed, Error-Preventing Expansion of Knowledge Graphs”, Springer Nature Switzerland AG, pp. 234-248 (2021).
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Point of Contact
Any inquiry concerning this communication or earlier communications from the examiner should be directed to HUBERT G CHEUNG whose telephone number is (571) 270-1396. The examiner can normally be reached M-R 8:00A-5:00P EST; alt. F 8:00A-4:00P EST.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Neveen Abel-Jalil can be reached at (571) 270-0474. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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HUBERT G. CHEUNG
Assistant Examiner
Art Unit 2152
Examiner: Hubert Cheung
/Hubert Cheung/Assistant Examiner, Art Unit 2152Date: April 5, 2026
/NEVEEN ABEL JALIL/Supervisory Patent Examiner, Art Unit 2152
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