DETAILED ACTION
This action is in response to the claims filed 03/13/2024 for Application number 18/604,352. Claims 1-20 are currently pending.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Regarding claim 1,
Step 1 Analysis: Claim 1 is directed to a process, which falls within one of the four statutory categories.
Step 2A Prong 1 Analysis: Claim 1 recites, in part, The limitations of:
the user intent identifying one or more elements of a knowledge graph or information usable to identify one or more elements of a knowledge graph can be considered to be an evaluation in the human mind,
generating a listener for the user intent can be considered to be an evaluation in the human mind
reviewing a knowledge graph or information describing changes to the knowledge graph to identify changes to knowledge graph elements comprised within the user intent; can be considered to be an evaluation in the human mind
with the listener for the user intent, identifying at least one change to at least one element of the knowledge graph specified in the user intent; can be considered to be an evaluation in the human mind
generating a message describing the at least one change; can be considered to be an evaluation in the human mind
These limitations as drafted, are processes that, under broadest reasonable interpretation, covers performance of the limitation in the mind or with the aid of pen and paper which falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
Step 2A Prong 2 Analysis: This judicial exception is not integrated into a practical application. In particular, the claim recites the additional elements - “at least one memory”, “one or more hardware processing units coupled to the at least one memory”, and “one or more computer readable storage media storing computer-executable instructions that, when executed, cause the computing system to perform operations”. Thus, these elements in the claim are recited at a high level of generality such that they amount to no more than mere instructions to apply the exception using a generic computer component. Please see MPEP 2106.05(f). Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
The claim further recites: receiving a definition of a user intent. This limitation is a mere data gathering step and thus is an insignificant extra-solution activity.
sending the message to be rendered for display to a user. This limitation is an insignificant extra-solution activity.
Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim as a whole is directed to an abstract idea.
Step 2B Analysis: The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of utilizing “at least one memory”, “one or more hardware processing units coupled to the at least one memory”, and “one or more computer readable storage media storing computer-executable instructions that, when executed, cause the computing system to perform operations to perform the steps of the claimed process amount to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Furthermore, the limitations of:
receiving a definition of a user intent and
sending the message to be rendered for display to a user.
are well-understood, routine, and conventional, as evidenced by MPEP §2106.05(d)(II)(I), “receiving or transmitting data over a network”. These limitations therefore remain insignificant extra-solution activity even upon reconsideration, and does not amount to significantly more. Even when considered in combination, these additional elements amount to mere instructions to apply the exception using generic computer components and insignificant extra-solution activity, which cannot provide an inventive concept. The claim is not patent eligible.
Regarding claim 2, the rejection of claim 1 is further incorporated, and further, the claim recites: wherein receiving a definition of a user intent comprises receiving user input, the user input identifying an element of the knowledge graph or information useable to identify an element of the knowledge graph. This limitation is an insignificant extra-solution activity and thus the judicial exception is not integrated into a practical application. The claim as a whole is directed to an abstract idea.
The claim does not include any additional elements that amount to significantly more than the judicial exception. This limitation is just a nominal or tangential addition to the claim, and is also well-understood, routine and conventional as evidenced by MPEP §2106.05(d)(II)(I), “receiving or transmitting data over a network”. This limitation therefore remains insignificant extra-solution activity even upon reconsideration, and does not amount to significantly more. Even when considered in combination, this additional element represents an insignificant extra-solution activity which cannot provide an inventive concept. The claim is not patent eligible.
Regarding claim 3, the rejection of claim 2 is further incorporated, and further, the claim recites: wherein the user input further comprises an identifier of the user intent and the identifier of the user intent and the identifier of the element of the knowledge graph or an identifier of an element of a knowledge graph determined with the information useable to identify an element of the knowledge graph are stored in a definition of the user intent. This limitation amounts to more specifics of the judicial exception identified in the rejection of claim 1 above.
The claim does not include any additional elements that amount to an integration of the judicial exception into a practical application, nor to significantly more than the judicial exception. The claim is not patent eligible.
Regarding claim 4, the rejection of claim 2 is further incorporated, and further, the claim recites: wherein the user input further specifies an interval, wherein the reviewing the knowledge graph or information describing changes to the knowledge graph is performed according to the interval. This limitation amounts to more specifics of the judicial exception identified in the rejection of claim 1 above.
The claim does not include any additional elements that amount to an integration of the judicial exception into a practical application, nor to significantly more than the judicial exception. The claim is not patent eligible.
Regarding claim 5, the rejection of claim 2 is further incorporated, and further, the claim recites: the operations further comprising: based on the element of the knowledge graph identified in the user input or an element of the knowledge graph identified using the information usable to identify an element of the knowledge graph, identifying at least one additional element of the knowledge graph and including the at least one additional element of the knowledge graph in the definition of the user intent, wherein the at least one additional element of the knowledge graph is not specified in the user input. This claim recites additional mental steps in addition to the judicial exception identified in the rejection of claim 1, thus recites a judicial exception.
The claim does not include any additional elements that amount to an integration of the judicial exceptions into a practical application, nor to significantly more than the judicial exceptions. The claim is not patent eligible.
Regarding claim 6, the rejection of claim 5 is further incorporated, and further, the claim recites: wherein the at least one additional element of the knowledge graph has a direct relationship with the element of the knowledge graph identified in the user input or the element of the knowledge graph identified using the information usable to identify an element of the knowledge graph. This limitation amounts to more specifics of the judicial exception identified in the rejection of claim 1 above.
The claim does not include any additional elements that amount to an integration of the judicial exception into a practical application, nor to significantly more than the judicial exception. The claim is not patent eligible.
Regarding claim 7, the rejection of claim 5 is further incorporated, and further, the claim recites: wherein the user input specifies a priority, and the priority is stored in the definition of the user intent, wherein the priority is used to determine elements of the knowledge graph to be included in the definition of the user intent and that are not specifically identified in the user input or directly identified from the information useable to identify an element of the knowledge graph. This limitation amounts to more specifics of the judicial exception identified in the rejection of claim 1 above.
The claim does not include any additional elements that amount to an integration of the judicial exception into a practical application, nor to significantly more than the judicial exception. The claim is not patent eligible.
Regarding claim 8, the rejection of claim 7 is further incorporated, and further, the claim recites: wherein determining elements of the knowledge graph that are not specifically identified in the user input comprises propagating at least a portion of the priority to knowledge graph elements and adding to the definition of the user intent knowledge graph elements having a priority value that satisfies a threshold. This claim recites additional mental steps in addition to the judicial exception identified in the rejection of claim 1, thus recites a judicial exception.
The claim does not include any additional elements that amount to an integration of the judicial exceptions into a practical application, nor to significantly more than the judicial exceptions. The claim is not patent eligible.
Regarding claim 9, the rejection of claim 2 is further incorporated, and further, the claim recites: wherein the element of the knowledge graph corresponds to an instance of a class represented in the knowledge graph. This limitation amounts to more specifics of the judicial exception identified in the rejection of claim 1 above.
The claim does not include any additional elements that amount to an integration of the judicial exception into a practical application, nor to significantly more than the judicial exception. The claim is not patent eligible.
Regarding claim 10, the rejection of claim 9 is further incorporated, and further, the claim recites: wherein the user input further comprises a restriction on a value of at least one property defined for the class, wherein knowledge graph changes are determined not to be relevant to the user intent when they relate the to the instance of the class and the value of the at least one property does not satisfy the restriction. This limitation amounts to more specifics of the judicial exception identified in the rejection of claim 1 above.
The claim does not include any additional elements that amount to an integration of the judicial exception into a practical application, nor to significantly more than the judicial exception. The claim is not patent eligible.
Regarding claim 11, the rejection of claim 9 is further incorporated, and further, the claim recites: wherein the generating the message comprises providing information describing the at least one change to a natural language generator. This limitation amounts to more specifics of the judicial exception identified in the rejection of claim 1 above.
The claim does recite the additional element of “natural language generator”, however it does not amount to an integration of the judicial exception into a practical application, nor to significantly more than the judicial exception, for the reasons set forth in connection with the rejection of claim 1 above. The claim is not patent eligible.
Regarding claim 12, the rejection of claim 11 is further incorporated, and further, the claim recites: wherein the information describing the at least one change is added to a prompt template and a prompt generated using the prompt template is provided to the natural language generator. This limitation amounts to more specifics of the judicial exception identified in the rejection of claim 1 above.
The claim does not include any additional elements that amount to an integration of the judicial exception into a practical application, nor to significantly more than the judicial exception. The claim is not patent eligible.
Regarding claim 13, the rejection of claim 1 is further incorporated, and further, the claim recites: receiving user input specifying a communication method to be used for notifications related to the user intent, wherein sending the message comprises sending the message using the communication method. This limitation is an insignificant extra-solution activity and thus the judicial exception is not integrated into a practical application. The claim as a whole is directed to an abstract idea.
The claim does not include any additional elements that amount to significantly more than the judicial exception. This limitation is just a nominal or tangential addition to the claim, and is also well-understood, routine and conventional as evidenced by MPEP §2106.05(d)(II)(I), “receiving or transmitting data over a network”. This limitation therefore remains insignificant extra-solution activity even upon reconsideration, and does not amount to significantly more. Even when considered in combination, this additional element represents an insignificant extra-solution activity which cannot provide an inventive concept. The claim is not patent eligible.
Regarding claim 14, the rejection of claim 1 is further incorporated, and further, the claim recites: wherein identifying at least one change to at least one element of the knowledge graph comprises scanning a log comprising log entries describing changes to the knowledge graph. This claim recites additional mental steps in addition to the judicial exception identified in the rejection of claim 1, thus recites a judicial exception.
The claim does not include any additional elements that amount to an integration of the judicial exceptions into a practical application, nor to significantly more than the judicial exceptions. The claim is not patent eligible.
Regarding claim 15, the rejection of claim 1 is further incorporated, and further, the claim recites: wherein the information describing changes to a knowledge graph is in the form of a triple identifying a class instance of the knowledge graph, a value of a property defined for the knowledge graph, and an identifier of the property. This limitation amounts to more specifics of the judicial exception identified in the rejection of claim 1 above.
The claim does not include any additional elements that amount to an integration of the judicial exception into a practical application, nor to significantly more than the judicial exception. The claim is not patent eligible.
Regarding claim 16, the rejection of claim 1 is further incorporated, and further, the claim recites: generating one or more triples from the user input, wherein a given triple of the one or more triples identifies a class instance of the knowledge graph, a value of a property defined for the knowledge graph, and an identifier of the property. This claim recites additional mental steps in addition to the judicial exception identified in the rejection of claim 1, thus recites a judicial exception.
The claim further recites: receiving user input comprising at least part of the definition; This limitation amounts to insignificant extra-solution activity.
The claim does not include any additional elements that amount to significantly more than the judicial exception. This limitation is just a nominal or tangential addition to the claim, and is also well-understood, routine and conventional as evidenced by MPEP §2106.05(d)(II)(I), “receiving or transmitting data over a network”. This limitation therefore remains insignificant extra-solution activity even upon reconsideration, and does not amount to significantly more. Even when considered in combination, this additional element represents an insignificant extra-solution activity which cannot provide an inventive concept. The claim is not patent eligible.
Regarding claim 17, the rejection of claim 1 is further incorporated, and further, the claim recites: wherein generating the message comprises linking at least one knowledge graph element described in the message to at least one document describing a change to the at least one knowledge graph element. This claim recites additional mental steps in addition to the judicial exception identified in the rejection of claim 1, thus recites a judicial exception.
The claim does not include any additional elements that amount to an integration of the judicial exceptions into a practical application, nor to significantly more than the judicial exceptions. The claim is not patent eligible.
Regarding Claim 18, it recites features similar to claim 1 and is rejected for at least the same reasons therein.
Regarding Claim 19, it recites features similar to claim 2 and is rejected for at least the same reasons therein.
Claim 20 recites features similar to claim 1 and is rejected for at least the same reasons therein. Claim 20 additionally requires analysis for “One or more non-transitory computer-readable storage media comprising: computer-executable instructions that, when executed by a computing system comprising at least one hardware processor and at least one memory coupled to the at least one hardware processor, cause the computing system to…” however this is an additional element that amounts to mere instructions to apply the judicial exception using a generic computer component. Please see MPEP 2106.05(f).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-6, 9-10, 13-14, and 17-20 are rejected under 35 U.S.C. 103 as being unpatentable over Shetty et al. ("US 20220215065 A1", hereinafter "Shetty") in view of Gupta et al. ("US 20210004711 A1", hereinafter "Gupta").
Regarding claim 1, Shetty teaches A computing system comprising:
at least one memory (¶0012, “memory storage”);
one or more hardware processing units coupled to the at least one memory (¶0012, “a memory storage and a computing device having a processor that executes instructions to carry out the stages described.”); and
one or more computer readable storage media storing computer-executable instructions that, when executed, cause the computing system to perform operations comprising (“The examples summarized above can each be incorporated into a non-transitory, computer-readable medium having instructions that, when executed by a processor associated with a computing device, cause the processor to perform the stages described.” [¶0012]):
receiving a definition of a user intent, the user intent identifying one or more elements of a knowledge graph or information usable to identify one or more elements of a knowledge graph (“] In one example, the browser 112 can provide an option where the user can specify event-based triggers (“user intent”) for monitoring. The event-based triggers can be linked to elements in the knowledge graph.” [¶0077]);
reviewing a knowledge graph or information describing changes to the knowledge graph to identify changes to knowledge graph elements comprised within the user intent (“The user can be alerted when a knowledge graph element changes that corresponds to an event-based trigger.” [¶0077]);
[with the listener for the user intent], identifying at least one change to at least one element of the knowledge graph specified in the user intent (“The user can be alerted when a knowledge graph element changes that corresponds to an event-based trigger.” [¶0077; see below: Betz teaches “a listener”]);
generating a message describing the at least one change (“As one example, where a user wants to know if the content on a web page changes, the notification can indicate which bookmarked web page the notification is for, such as with the web page's title and/or URL, and indicate the change that occurred.” [¶0081]); and
sending the message to be rendered for display to a user (“ At stage 516, the browser 112, or push server, can notify the user of the change. The bookmark management service 126 can use other methods to notify the user as well, such as by sending an email or a text message.” [¶0080]).
However fails to explicitly teach generating a listener for the user intent;
Gupta teaches generating a listener for the user intent; (“In one or more examples, the GUI indicates at least the following: a. sequence of operations, with each operation corresponding to an entity; b. based on the entity name, intents are identified based on the conversation terms used; and c. event listeners which monitor changes in the process representation 105 are identified.” [¶0109])
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Shetty’s teachings in order to generate a listener for a user intent as taught by Gupta. One would have been motivated to make this modification in order to address such technical challenges during the development of an RPA system, and solve the technical problems by optimizing a process and decision-making using machine learning or artificial intelligence (AI). [¶0036, Gupta]
Regarding claim 2, Shetty/Gupta teaches The computing system of claim 1, Shetty further teaches wherein receiving a definition of a user intent comprises receiving user input, the user input identifying an element of the knowledge graph or information useable to identify an element of the knowledge graph. (“In one example, the browser 112 can provide an option where the user can specify event-based triggers for monitoring. The event-based triggers can be linked to elements in the knowledge graph.” [¶0077])
Regarding claim 3, Shetty/Gupta teaches The computing system of claim 2, Shetty further teaches wherein the user input further comprises an identifier of the user intent and the identifier of the user intent and the identifier of the element of the knowledge graph or an identifier of an element of a knowledge graph determined with the information useable to identify an element of the knowledge graph are stored in a definition of the user intent. (“The user can provide the names or other identifiers of people for whom he would like to be notified if any of them register for the event. A user can also select to be notified if any date or location information for the event change on the bookmarked page.” [¶0077])
Regarding claim 4, Shetty/Gupta teaches The computing system of claim 2, Shetty teaches wherein the user input further specifies an interval, wherein the reviewing the knowledge graph or information describing changes to the knowledge graph is performed according to the interval (“At stage 510, the bookmark management service 126 can monitor the web page for changes.. In one example, the browser 112 can allow the user to configure how frequently the bookmark management service 126 checks the web page for changes” [¶0078])
Regarding claim 5, Shetty/Gupta teaches The computing system of claim 2, Shetty teaches the operations further comprising: based on the element of the knowledge graph identified in the user input or an element of the knowledge graph identified using the information usable to identify an element of the knowledge graph, identifying at least one additional element of the knowledge graph and including the at least one additional element of the knowledge graph in the definition of the user intent, wherein the at least one additional element of the knowledge graph is not specified in the user input. (“The bookmark management service 126 can associate tags with various elements of the web page, and then bookmark management service 126 can compare the tags with tags associated with the other web pages previously bookmarked under the user's profile.” [¶0044; implied that additional tags of elements associated with the user would not be specified in the user input)
Regarding claim 6, Shetty/Gupta teaches The computing system of claim 5, Shetty teaches wherein the at least one additional element of the knowledge graph has a direct relationship with the element of the knowledge graph identified in the user input or the element of the knowledge graph identified using the information usable to identify an element of the knowledge graph. (“The bookmark management service 126 can associate tags with various elements of the web page, and then bookmark management service 126 can compare the tags with tags associated with the other web pages previously bookmarked under the user's profile. Based on the comparison, the bookmark management service 126 can identify a bookmarked web page that exceeds a threshold matching score. The bookmark management service 126 can apply the ML model 124 to perform a sematic similarity analysis between the two pages” [¶0044; similarity corresponds to a “direct relationship”])
Regarding claim 9, Shetty/Gupta teaches The computing system of claim 2, Shetty teaches wherein the element of the knowledge graph corresponds to an instance of a class represented in the knowledge graph. (“In an example, the bookmark management service 126 can implement one or multiple classification types to categorize the web page and associate tags.” [¶0029])
Regarding claim 10, Shetty/Gupta teaches The computing system of claim 9, Shetty teaches wherein the user input further comprises a restriction on a value of at least one property defined for the class, wherein knowledge graph changes are determined not to be relevant to the user intent when they relate the to the instance of the class and the value of the at least one property does not satisfy the restriction. (“In an example, the ML model 124 can perform a semantic similarity analysis to categorize the similarity of the two web pages. For example, the ML model 124 can output whether the web pages are the same, similar, or different.” [¶0041; different webpages would correspond to not satisfying the restriction and would not be relevant to the user intent])
Regarding claim 13, Shetty/Gupta teaches The computing system of claim 1, Shetty teaches the operations further comprising: receiving user input specifying a communication method to be used for notifications related to the user intent, wherein sending the message comprises sending the message using the communication method.(“ The bookmark management service 126 can use other methods to notify the user as well, such as by sending an email or a text message.” [¶0080, See abstract “user device”])
Regarding claim 14, Shetty/Gupta teaches The computing system of claim 1, Shetty teaches wherein identifying at least one change to at least one element of the knowledge graph comprises scanning a log comprising log entries describing changes to the knowledge graph. (“The bookmark management service 126 can do a similar analysis in checking for certain users on an event registration page or monitoring certain content on the event page for changes. In one example, the browser 112 can allow the user to configure how frequently the bookmark management service 126 checks the web page for changes.” [¶0078; scanning a log is implied in order to track web page changes])
Regarding claim 17, Shetty/Gupta teaches The computing system of claim 1, Shetty teaches wherein generating the message comprises linking at least one knowledge graph element described in the message to at least one document describing a change to the at least one knowledge graph element. (“For example, if the user wants to know if a particular coworker adds or modifies a document in a shared folder, the bookmark management service 126 can periodically construct a new knowledge graph of the web page and check for any elements in the knowledge graph pertaining to that user adding or modified a document.” [¶0078])
Regarding claim 18, it is substantially similar to claim 1 respectively, and is rejected in the same manner, the same art, and reasoning applying.
Regarding claim 19, it is substantially similar to claim 2 respectively, and is rejected in the same manner, the same art, and reasoning applying.
Claim 20 recites features similar to claim 1 and is rejected for at least the same reasons therein. Claim 20 additionally requires One or more non-transitory computer-readable storage media comprising: computer-executable instructions that, when executed by a computing system comprising at least one hardware processor and at least one memory coupled to the at least one hardware processor, cause the computing system to… (Shetty, ¶0012)
Claim 7, 8 and 11 are rejected under 35 U.S.C. 103 as being unpatentable over Shetty in view of Gupta and further in view of Mac an tSaoir et al. ("US 20170024460 A1", hereinafter "Mac").
Regarding claim 7, Shetty/Gupta teaches The computing system of claim 5, however fails to explicitly teach wherein the user input specifies a priority, and the priority is stored in the definition of the user intent, wherein the priority is used to determine elements of the knowledge graph to be included in the definition of the user intent and that are not specifically identified in the user input or directly identified from the information useable to identify an element of the knowledge graph.
Mac teaches wherein the user input specifies a priority (“In the illustrated embodiment, search engine 100 is configured to take a search expression input from a user, which includes search terms” [¶0057, See further ¶0022 for “priority”]), and the priority is stored in the definition of the user intent (“a focus engine for determining a center of focus for the two or more determined nodes in the semantic graph by a process of spreading activation in the semantic graph;” [¶0022]), wherein the priority is used to determine elements of the knowledge graph to be included in the definition of the user intent and that are not specifically identified in the user input or directly identified from the information useable to identify an element of the knowledge graph. (“In the illustrated embodiment, context comparator 212 is configured to determine the contextual relevance for the determined nodes and surrounding nodes by assessing semantic similarity with respect to the center of focus… In one embodiment and scenario, expansion candidate selector 214 is thus configured to select one or more expansion candidates based on the contextual relevance for the nodes and expansion candidates.” [¶0068-¶0069])
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Shetty’s/Gupta’s teachings in order to implement the weighted signals and selection of related graph elements based on the relevance of the user input as taught by Mac. One would have been motivated to make this modification to improve information retrieval and natural language processing by identifying related concepts based on a focus. [¶0003, Mac]
Regarding claim 8, Shetty/Gupta/Mac teaches The computing system of claim 7, where Mac teaches wherein determining elements of the knowledge graph that are not specifically identified in the user input comprises propagating at least a portion of the priority to knowledge graph elements (“Spreading activation engine 209 activates determined nodes in the graph structure and propagates a spreading signal through the graph from these starting points.” [¶0066]) and adding to the definition of the user intent knowledge graph elements having a priority value that satisfies a threshold. (“In the illustrated embodiment, context comparator 212 is configured to determine the contextual relevance for the determined nodes and surrounding nodes by assessing semantic similarity with respect to the center of focus… In the illustrated embodiment, expansion candidate selector 214 is configured to i) select a determined node with highest contextual relevance for each query term, and ii) filter selected nodes for contextual relevance over a threshold.” [¶0068-¶0069)
Same motivation to combine the teachings of Shetty/Gupta/Mac as claim 7.
Regarding claim 11, Shetty/Gupta teaches The computing system of claim 1, however fails to explicitly teach wherein the generating the message comprises providing information describing the at least one change to a natural language generator.
Mac teaches wherein the generating the message comprises providing information describing the at least one change to a natural language generator.
(“In some embodiments and scenarios, upon receipt of a user query, the text is processed using standard natural language processing techniques for lexical analysis and concept identification.” [¶0078])
Same motivation to combine the teachings of Shetty/Gupta/Mac as claim 7.
Claim 12 is rejected under 35 U.S.C. 103 as being unpatentable over Shetty in view of Gupta and Mac and further in view of Pan et al. ("Large Language Models and Knowledge Graphs: Opportunities and Challenges", hereinafter "Pan").
Regarding claim 12, Shetty/Gupta/Mac The computing system of claim 11, however fails to explicitly teach wherein the information describing the at least one change is added to a prompt template and a prompt generated using the prompt template is provided to the natural language generator.
Pan teaches wherein the information describing the at least one change is added to a prompt template and a prompt generated using the prompt template is provided to the natural language generator. (“Currently LLM fine-tuning-based methods can well utilize the text of individual entities, but their other formal semantics are often ignored or not effectively incorporated. Besides fine tuning with samples constructed by some templates, more LLM techniques such as prompt learning and instruction tuning could be considered.” [pg. 15, 4.3.2, bottom bullet])
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Shetty’s/Gupta’s/Mac’s teachings by implementing the prompt engineering techniques disclosed within the disclosure of Pan. One would have been motivated to make this modification as a popular approach for explicit knowledge representation, KGs are now widely investigated for the combination with Transformer-based LLMs, including pre-trained masked language models (PLMs) like BERT [39] and RoBERTa [104], and more recent generative LLMs like the GPT series [23] and LLaMA [165]. [pg. 2, 1. Introduction, Pan]
Claims 15 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Shetty in view of Gupta and further in view of Pan.
Regarding claim 15, Shetty/Gupta teaches The computing system of claim 1, however fails to explicitly teach wherein the information describing changes to a knowledge graph is in the form of a triple identifying a class instance of the knowledge graph, a value of a property defined for the knowledge graph, and an identifier of the property.
Pan teaches wherein the information describing changes to a knowledge graph is in the form of a triple identifying a class instance of the knowledge graph, a value of a property defined for the knowledge graph, and an identifier of the property. (“Link prediction is about predicting a missing element of a triple given the other two elements. It includes head entity prediction (?,r,t), relation prediction (h,?,t), and tail prediction (h,r,?).” [pg. 8, 4.2.1, Link Prediction])
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Shetty’s/Gupta’s teachings by implementing the prompt engineering techniques disclosed within the disclosure of Pan. One would have been motivated to make this modification as a popular approach for explicit knowledge representation, KGs are now widely investigated for the combination with Transformer-based LLMs, including pre-trained masked language models (PLMs) like BERT [39] and RoBERTa [104], and more recent generative LLMs like the GPT series [23] and LLaMA [165]. [pg. 2, 1. Introduction, Pan]
Regarding claim 16, Shetty/Gupta teaches The computing system of claim 1, Shetty teaches the operations further comprising:
receiving user input comprising at least part of the definition; (See ¶0077)
however fails to explicitly teach and
generating one or more triples from the user input, wherein a given triple of the one or more triples identifies a class instance of the knowledge graph, a value of a property defined for the knowledge graph, and an identifier of the property.
Pan teaches generating one or more triples from the user input, wherein a given triple of the one or more triples identifies a class instance of the knowledge graph, a value of a property defined for the knowledge graph, and an identifier of the property. (See pg. 11-12, Prompt Engineering for Triple Extraction and §4.4. “Firstly, KGs can be used as training data for LLMs. Secondly, triples in KGs can be used for prompt construction. Last but not least, KGs can be used as external knowledge in retrieval augmented language models.” [pg. 16])
Same motivation to combine Shetty/Gupta/Pan as claim 15.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MICHAEL H HOANG whose telephone number is (571)272-8491. The examiner can normally be reached Mon-Fri 8:30AM-4:30PM.
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, Kakali Chaki can be reached at (571) 272-3719. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/MICHAEL H HOANG/PRIMARY EXAMINER, Art Unit 2122
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