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 action is responsive to the application filed on May 5th, 2023. Claims 1-20 are pending in the case. Claims 1, 11 and 19 are independent claims.
Information Disclosure Statement
The information disclosure statement filed August 29th, 2023 fails to comply with the provisions of 37 CFR 1.97, 1.98 and MPEP § 609 because US 20220026987 A1 is cited with “Liu et al.” listed as the first named inventor, however Liu is not listed as an inventor on the patent application. It has been placed in the application file, but the information referred to therein has not been considered as to the merits. Applicant is advised that the date of any re-submission of any item of information contained in this information disclosure statement or the submission of any missing element(s) will be the date of submission for purposes of determining compliance with the requirements based on the time of filing the statement, including all certification requirements for statements under 37 CFR 1.97(e). See MPEP § 609.05(a).
The remainder of the information disclosure statement filed August 29th, 2023 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the further patents and patent publications listed therein are being considered by the examiner.
Specification
The use of the terms: NVLINK and NVSwitch in ¶80, Wi-Fi, Z-Wave, Bluetooth, Bluetooth LE, ZigBee, InfiniBand, LoRaWAN and SigFox, in ¶83, Amazon Web Services, Google Cloud and Microsoft Azure in ¶92, PyTorch, TensorFlow and Caffe in ¶94 which are trade names or marks used in commerce, have been noted in this application. The terms should be accompanied by the generic terminology; furthermore the terms should be capitalized wherever it appears or, where appropriate, include a proper symbol indicating use in commerce such as ™, SM , or ® following the terms.
Although the use of trade names and marks used in commerce (i.e., trademarks, service marks, certification marks, and collective marks) are permissible in patent applications, the proprietary nature of the marks should be respected and every effort made to prevent their use in any manner which might adversely affect their validity as commercial marks.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitations uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitations are:
“processing units to” in claim 11.
“processing units to” in claim 19.
Because these claim limitations are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, they are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have these limitations interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitations to avoid them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitations recite sufficient structure to perform the claimed function so as to avoid them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 112
Claim limitations “processing units to” in claim 11 and “processing units to” in claim 19 invokes 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for performing the entire claimed function and to clearly link the structure, material, or acts to the function. No association between the structure and the function can be found in the specification. Therefore, the claim is indefinite and is rejected under 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph.
Applicant may:
(a) Amend the claim so that the claim limitation will no longer be interpreted as a limitation under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph;
(b) Amend the written description of the specification such that it expressly recites what structure, material, or acts perform the entire claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(c) Amend the written description of the specification such that it clearly links the structure, material, or acts disclosed therein to the function recited in the claim, without introducing any new matter (35 U.S.C. 132(a)).
If applicant is of the opinion that the written description of the specification already implicitly or inherently discloses the corresponding structure, material, or acts and clearly links them to the function so that one of ordinary skill in the art would recognize what structure, material, or acts perform the claimed function, applicant should clarify the record by either:
(a) Amending the written description of the specification such that it expressly recites the corresponding structure, material, or acts for performing the claimed function and clearly links or associates the structure, material, or acts to the claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(b) Stating on the record what the corresponding structure, material, or acts, which are implicitly or inherently set forth in the written description of the specification, perform the claimed function. For more information, see 37 CFR 1.75(d) and MPEP §§ 608.01(o) and 2181.
Claims 12-18 and 20 are rejected for being dependent on a rejected base claim without curing any of the deficiencies.
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: Claim 1 is directed to A method, therefore it falls under the statuary category of a process.
Step 2A Prong 1: The claim recites, in part:
“determining, …based at least on first data representative of a request, at least a first entity associated with the request” this encompasses the mental determination an entity associated with an observed request.
“determining, …a first embedding associated with the first entity” this encompasses the mental determination of an embedding associated with an observed entity. Further, this limitation is a mathematical concept.
“determining, based at least on the first embedding and one or more second embeddings associated with one or more of second entities, that the first entity is related to a second entity of the one or more second entities” this encompasses the mental determination that two observed entities are related.
“generating, based at least on at least one of the first entity or the second entity, second data representative of a response to the request” this encompasses the mental creation of data representative of an observed request based on observed entities.
Step 2A Prong 2: The judicial exception is not integrated into a practical application; the remaining limitations of the claim are as follows: “using one or more machine learning models”, “using the one or more machine learning models” the limitations are an additional element that amounts to adding the words “apply it” (or an equivalent) with the judicial exception, or merely uses a computer in its ordinary capacity as a tool to perform an existing process. See MPEP § 2106.05(f)(2).
Step 2B: The additional elements, taken individually and in combination, do not provide an inventive concept of significantly more than the abstract idea itself for the reasons set forth in step 2A prong 2 above. Therefore, the claim is ineligible.
Regarding claim 2, the rejection of claim 1 is incorporated and further:
Step 2A Prong 1: The claim recites, in part:
“determining, based at least on the first embedding and the one or more second embeddings associated with the one or more of second entities, one or more values indicating one or more similarities between the first entity and the one or more second entities” this encompasses the mental determination of a similarity between observed entities based on observed embeddings. Further, this limitation is a mathematical concept.
“determining, based at least on the one or more values, that the first entity is related to the second entity” this encompasses the mental determination that two observed entities are related based on observed values.
Step 2A Prong 2: The claim does not recite any additional limitations, thus does not further recite any additional elements that integrates the judicial exception into a practical application or amount to significantly more.
Regarding claim 3, the rejection of claim 1 is incorporated and further:
Step 2A Prong 1: The claim recites, in part:
“determining, based at least on comparing the first embedding to the one or more second embeddings associated with the one or more of second entities, one or more values indicating one or more similarities between the first entity and the one or more second entities” this encompasses the mental determination that, based on a comparison between observed embeddings, values indicating the similarity of observed entities. Further, this limitation is a mathematical concept.
“determining that the second entity is associated with a value of the one or more values that satisfies a threshold value” this encompasses the mental determination that an observed entity is associated with an observed value. Further, this limitation is a mathematical concept.
“determining, based at least on the second entity being associated with the value that satisfies the threshold value, that the first entity is related to the second entity” this encompasses the mental determination that two observed entities are related based on an observed value. Further, this limitation is a mathematical concept.
Step 2A Prong 2: The claim does not recite any additional limitations, thus does not further recite any additional elements that integrates the judicial exception into a practical application or amount to significantly more.
Regarding claim 4, the rejection of claim 1 is incorporated and further:
Step 2A Prong 1: The claim recites, in part:
“determining, …based at least on the first data representative of the request, that the first entity is associated with an entity category” this encompasses the mental determination that an observed entity is associated with a category.
“the one or more second entities are also associated with the entity category, and wherein the determining that the first entity is related to the second entity is further based at least on the first entity and the one or more second entities being associated with the entity category” this encompasses the mental determination that two observed entities are related based on observed categories.
Step 2A Prong 2: The judicial exception is not integrated into a practical application; the remaining limitations of the claim are as follows: “using the one or more machine learning models” the limitation is an additional element that amounts to adding the words “apply it” (or an equivalent) with the judicial exception, or merely uses a computer in its ordinary capacity as a tool to perform an existing process. See MPEP § 2106.05(f)(2).
Step 2B: The additional elements, taken individually and in combination, do not provide an inventive concept of significantly more than the abstract idea itself for the reasons set forth in step 2A prong 2 above. Therefore, the claim is ineligible.
Regarding claim 5, the rejection of claim 1 is incorporated and further:
Step 2A Prong 1: The claim recites, in part:
“determining, based at least on the first embedding and one or more third embeddings associated with one or more of third entities, that the first entity is not related to the one or more third entities” this encompasses the mental determination that an entity is not related to other observed entities based on observed embeddings.
“the determining that the first entity is related to the second entity occurs based at least on the first entity not being related to the one or more third entities” this encompasses the mental determination that two observed entities are related due to their not being related to a third observed entity.
Step 2A Prong 2: The claim does not recite any additional limitations, thus does not further recite any additional elements that integrates the judicial exception into a practical application or amount to significantly more.
Regarding claim 6, the rejection of claim 5 is incorporated and further:
Step 2A Prong 1: The claim recites, in part:
“the one or more third entities are associated with a first entity category” a continuation of the abstract idea identified in the parent claim.
“the one or more second entities are associated with a second entity category that is related to the first entity category” a continuation of the abstract idea identified in the parent claim.
“determining that the first entity is related to the second entity further occurs based at least on the second entity category being related to the first entity category” this encompasses the mental determination that two entities are related based on an observed category.
Step 2A Prong 2: The claim does not recite any additional limitations, thus does not further recite any additional elements that integrates the judicial exception into a practical application or amount to significantly more.
Regarding claim 7, the rejection of claim 1 is incorporated and further:
Step 2A Prong 1: The claim recites, in part:
Step 2A Prong 2: The judicial exception is not integrated into a practical application; the remaining limitations of the claim are as follows: “receiving a template associated with the response, the template including at least one or more words and one or more slots associated with inputting one or more entities” the limitation is an additional element that amounts to adding insignificant extra-solution activity to the judicial exception. See MPEP § 2106.05(g).
“generating the second data representative of the response by inputting the at least one of the first entity or the second entity into the one or more slots” this encompasses the mental creation of a response by filling slots in an observed template.
Step 2B: The additional element “receiving a template associated with the response, the template including at least one or more words and one or more slots associated with inputting one or more entities” is an additional element that amounts to adding insignificant extra-solution activity to the judicial exception. See MPEP § 2106.05(g). Furthermore the additional element is directed to receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d. Therefore, the claim is ineligible.
Regarding claim 8, the rejection of claim 1 is incorporated and further:
Step 2A Prong 1: The claim recites, in part:
“generating, …based at least on the first data representative of the request, the first entity, and the second entity, the second data representative of the response to the request” this encompasses the mental creation of a response to an observed request.
Step 2A Prong 2: The judicial exception is not integrated into a practical application; the remaining limitations of the claim are as follows: “using one or more large language models (LLMs)” the limitation is an additional element that amounts to adding the words “apply it” (or an equivalent) with the judicial exception, or merely uses a computer in its ordinary capacity as a tool to perform an existing process. See MPEP § 2106.05(f)(2).
Step 2B: The additional elements, taken individually and in combination, do not provide an inventive concept of significantly more than the abstract idea itself for the reasons set forth in step 2A prong 2 above. Therefore, the claim is ineligible.
Regarding claim 9, the rejection of claim 1 is incorporated and further:
Step 2A Prong 1: a continuation of the abstract idea identified in the parent claim.
Step 2A Prong 2: The judicial exception is not integrated into a practical application; the remaining limitations of the claim are as follows: “the determining the at least the first entity associated with the request uses one or more first machine learning models of the one or more machine learning models”, “the determining the first embedding associated with the first entity uses one or more second machine learning models of the one or more machine learning models” the limitations are an additional element that amounts to adding the words “apply it” (or an equivalent) with the judicial exception, or merely uses a computer in its ordinary capacity as a tool to perform an existing process. See MPEP § 2106.05(f)(2).
Step 2B: The additional elements, taken individually and in combination, do not provide an inventive concept of significantly more than the abstract idea itself for the reasons set forth in step 2A prong 2 above. Therefore, the claim is ineligible.
Regarding claim 10, the rejection of claim 1 is incorporated and further:
Step 2A Prong 1: The claim recites, in part:
“the response includes at least a first word associated with the second entity; or the response includes at least a second word associated with a third entity that is related to the second entity” a continuation of the abstract idea identified in the parent claim.
Step 2A Prong 2: The claim does not recite any additional limitations, thus does not further recite any additional elements that integrates the judicial exception into a practical application or amount to significantly more.
Regarding claim 11:
Step 1: Claim 11 is directed to A system, therefore it falls under the statuary category of a machine.
Step 2A Prong 1: The claim recites, in part:
“determine, …based at least on first data representative of a request, at least a first entity associated with the request” this encompasses the mental determination an entity associated with an observed request.
“determine, …a first embedding associated with the first entity” this encompasses the mental determination of an embedding associated with an observed entity. Further, this limitation is a mathematical concept.
“determine, based at least on a latent space comparison between the first embedding and one or more second embeddings associated with one or more of second entities, that the first entity is related to a second entity of the one or more second entities” this encompasses the mental determination that two observed entities are related. Further, this limitation is a mathematical concept.
“output, based at least on at least one of the first entity or the second entity, second data representative of a response to the request” this encompasses the mental creation of data representative of an observed request based on observed entities.
Step 2A Prong 2: The judicial exception is not integrated into a practical application; the remaining limitations of the claim are as follows: “one or more processing units to”, “using one or more machine learning models”, “using the one or more machine learning models” the limitations are an additional element that amounts to adding the words “apply it” (or an equivalent) with the judicial exception, or merely uses a computer in its ordinary capacity as a tool to perform an existing process. See MPEP § 2106.05(f)(2).
Step 2B: The additional elements, taken individually and in combination, do not provide an inventive concept of significantly more than the abstract idea itself for the reasons set forth in step 2A prong 2 above. Therefore, the claim is ineligible.
Regarding claims 12-15:
The rejection of claim 11 is further incorporated, the rejection of claims 2-5 are applicable to claims 12-15, respectively.
Regarding claim 16, the rejection of claim 11 is incorporated and further:
Step 2A Prong 1: The claim recites, in part:
“generate the second data representative of the response by at least inputting the at least one of the first entity or the second entity into one or more slots of a template associated with the response” this encompasses the mental creation of data by inputting observed entities into an observed template.
“generate, …based at least on the first data representative of the request, the first entity, and the second entity, the second data representative of the response to the request” this encompasses the mental creation of a response to an observed request based on observed entities.
Step 2A Prong 2: The judicial exception is not integrated into a practical application; the remaining limitations of the claim are as follows: “using one or more second machine learning models” the limitation is an additional element that amounts to adding the words “apply it” (or an equivalent) with the judicial exception, or merely uses a computer in its ordinary capacity as a tool to perform an existing process. See MPEP § 2106.05(f)(2).
Step 2B: The additional elements, taken individually and in combination, do not provide an inventive concept of significantly more than the abstract idea itself for the reasons set forth in step 2A prong 2 above. Therefore, the claim is ineligible.
Regarding claim 17:
The rejection of claim 11 is further incorporated, the rejection of claim 9 is applicable to claim 17.
Regarding claim 18, the rejection of claim 11 is incorporated and further:
Step 2A Prong 1: a continuation of the abstract idea identified in the parent claim.
Step 2A Prong 2: The judicial exception is not integrated into a practical application; the remaining limitations of the claim are as follows: “a control system for an autonomous or semi-autonomous machine; a perception system for an autonomous or semi-autonomous machine; a system for performing simulation operations; a system for performing digital twin operations; a system for performing light transport simulation; a system for performing collaborative content creation for 3D assets; a system for performing deep learning operations; a system implemented using an edge device; a system implemented using a robot; a system for performing conversational AI operations; a system implementing one or more large language models (LLMs); a system for generating synthetic data; a system incorporating one or more virtual machines (VMs); a system implemented at least partially in a data center; or a system implemented at least partially using cloud computing resources.” These limitations are an additional element that generally links the use of the judicial exception to a particular technological environment or field of use. See MPEP § 2106.05(h).
Step 2B: The additional elements, taken individually and in combination, do not provide an inventive concept of significantly more than the abstract idea itself for the reasons set forth in step 2A prong 2 above. Therefore, the claim is ineligible.
Regarding claim 19:
Step 1: Claim 19 is directed to A processor, therefore it falls under the statuary category of a manufacture.
Step 2A Prong 1: The claim recites, in part:
“generate first data representative of a response associated with a request, wherein the response is generated based at least on a first entity included in the request and a second entity that is related to the first entity, the first entity being related to the second entity based at least on a first embedding associated with the first entity and a second embedding associated with the second entity” this encompasses the mental generation of a response to an observed request based on observed entities and embeddings. Further, this limitation is a mathematical concept.
Step 2A Prong 2: The judicial exception is not integrated into a practical application; the remaining limitations of the claim are as follows: “one or more processing units to” the limitation is an additional element that amounts to adding the words “apply it” (or an equivalent) with the judicial exception, or merely uses a computer in its ordinary capacity as a tool to perform an existing process. See MPEP § 2106.05(f)(2).
Step 2B: The additional elements, taken individually and in combination, do not provide an inventive concept of significantly more than the abstract idea itself for the reasons set forth in step 2A prong 2 above. Therefore, the claim is ineligible.
Regarding claim 20:
The rejection of claim 19 is further incorporated, the rejection of claim 18 is applicable to claim 20.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-6 and 7-20 are rejected under 35 U.S.C. 103 as being unpatentable over Joko et al. ("Conversational Entity Linking: Problem Definition and Datasets", Joko et al., 11 July 2021) hereinafter Joko in view of Mandel et al. (US 11200885 B1) hereinafter Mandel.
Regarding claim 1:
Joko teaches A method comprising: determining, using one or more machine learning models and based at least on first data…, at least a first entity associated with the request (Joko, page 7, col 2, section 6, ¶1 “In this paper, we studied entity linking in a broad setting of conversational systems: QA, task-oriented, and social chat.” Further, Joko, page 3, col 1, ¶1 “These cover the three main categories of conversational problems [30]: question answering (QA), task-oriented systems, and social chat (cf. Sect. 3).” Here, the entity linked in a question answering (QA) problem can be considered a request);
determining, using the one or more machine learning models, a first embedding associated with the first entity (Joko, page 5, col 2, section 4.2, ¶1 “Once this mapping was done, mention-entity pairs can be identified as described in Stage 1 of Section 4.1.” here, the mapped mention-entity pairs can be considered the embedding);
determining, based at least on the first embedding and one or more second embeddings associated with one or more of second entities, that the first entity is related to a second entity of the one or more second entities (Joko, page 7, col 1, ¶4 “Considering a personal entity mention mpe , and an entity e, the PE method computes the cosine similarity between the word embedding of mpe and the entity embedding of entity e. For every mpe, we compute this similarity with all the previously linked entities in the conversation and find the most similar entity.” Here, the first entity can be considered related to the second entity if it is the most similar entity and further, Specification, ¶42 “For instance, in some examples, the association component 118 may perform cosine similarity to determine cosine similarity values between the embedding associated with the entity and the embeddings associated with the stored entities.”);
Joko does not teach "…representative of a request
generating, based at least on at least one of the first entity or the second entity, second data representative of a response to the request."
However, Mandel teaches …representative of a request (Mandel, col 13, lines 22-25 “Further continuing the example above, the NLG system may select a template in response to the question, “What is the weather currently like?” of the form: “The weather currently is $weather_information$.”” Here, the question regarding the weather can be considered the request)
generating, based at least on at least one of the first entity or the second entity, second data representative of a response to the request (Mandel, col 13, lines 22-25 “Further continuing the example above, the NLG system may select a template in response to the question, “What is the weather currently like?” of the form: “The weather currently is $weather_information$.””).
Joko and Mandel are analogous art because both references concern methods for entity linking in conversational systems. Accordingly, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to modify Joko’s conversational entity linking system to incorporate the request and response taught by Mandel. The motivation for doing so would have been to process and perform tasks based on commands as stated in Mandel, col 1, lines 8-12 “Speech-recognition processing combined with natural-language understanding processing enables voice-based control of a computing device to perform tasks based on the user's spoken commands.”
Regarding claim 2:
Joko in view of Mandel teaches The method of claim 1, wherein the determining that the first entity is related to the second entity comprises:
determining, based at least on the first embedding and the one or more second embeddings associated with the one or more of second entities, one or more values indicating one or more similarities between the first entity and the one or more second entities (Joko, page 7, col 1, ¶4 “For every mpe, we compute this similarity with all the previously linked entities in the conversation and find the most similar entity.”); and
determining, based at least on the one or more values, that the first entity is related to the second entity (Joko, page 7, col 1, ¶4 “Mention-entity pairs 〈mpe, e〉 below a certain threshold τ are ignored. This threshold allows for filtering personal entity mentions that do not have the corresponding entities in the conversation history.”).
Regarding claim 3:
Joko in view of Mandel teaches The method of claim 1, wherein the determining that the first entity is related to the second entity comprises:
determining, based at least on comparing the first embedding to the one or more second embeddings associated with the one or more of second entities, one or more values indicating one or more similarities between the first entity and the one or more second entities (Joko, page 7, col 1, ¶4 “Considering a personal entity mention mpe , and an entity e, the PE method computes the cosine similarity between the word embedding of mpe and the entity embedding of entity e.” In light of the, Specification, ¶42 “For instance, in some examples, the association component 118 may perform cosine similarity to determine cosine similarity values between the embedding associated with the entity and the embeddings associated with the stored entities.”;
determining that the second entity is associated with a value of the one or more values that satisfies a threshold value (Joko, page 7, col 1, ¶4 “Mention-entity pairs 〈mpe, e〉 below a certain threshold τ are ignored. This threshold allows for filtering personal entity mentions that do not have the corresponding entities in the conversation history.”); and
determining, based at least on the second entity being associated with the value that satisfies the threshold value, that the first entity is related to the second entity (Joko, page 7, col 1, ¶4 “This threshold allows for filtering personal entity mentions that do not have the corresponding entities in the conversation history.” Here, those values ).
Regarding claim 4:
Joko in view of Mandel teaches The method of claim 1, further comprising:
determining, using the one or more machine learning models and based at least on the first data representative of the request, that the first entity is associated with an entity category (Mandel, col 6, lines 21-25 “If, for example, the text data corresponds to “what is the weather,” the dialog manager 260 may determine that that the system(s) 120 is to output weather information associated with a geographic location of the device 110 a. In another example, if the text data corresponds to “turn off the lights,” the dialog manager 260 may determine that the system(s) 120 is to turn off lights associated with the device(s) 110 a or the user(s) 5.” Here, the weather or lights can be considered the category in light of the specification, ¶18 “In such an example, the food category entities may be associated with specific entities, such as the food names entity being associated with a burger entity, a pizza entity, and a salad entity.”),
wherein the one or more second entities are also associated with the entity category, and wherein the determining that the first entity is related to the second entity is further based at least on the first entity and the one or more second entities being associated with the entity category (Mandel, col 6, lines 25-28 “In another example, if the text data corresponds to “turn off the lights,” the dialog manager 260 may determine that the system(s) 120 is to turn off lights associated with the device(s) 110 a or the user(s) 5.” Here, the lights associated with the user can be considered the second entity related to the entity category).
Joko and Mandel are analogous art because both references concern methods for entity linking in conversational systems. Accordingly, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to modify Joko’s conversational entity linking system to incorporate the categories taught by Mandel. The motivation for doing so would have been to process and perform tasks based on commands as stated in Mandel, col 1, lines 8-12 “Speech-recognition processing combined with natural-language understanding processing enables voice-based control of a computing device to perform tasks based on the user's spoken commands.”
Regarding claim 5:
Joko in view of Mandel teaches The method of claim 1, further comprising:
determining, based at least on the first embedding and one or more third embeddings associated with one or more of third entities, that the first entity is not related to the one or more third entities (Joko, page 7, col 1, ¶4 “For every mpe, we compute this similarity with all the previously linked entities in the conversation and find the most similar entity. Mention-entity pairs 〈mpe, e〉 below a certain threshold τ are ignored. This threshold allows for filtering personal entity mentions that do not have the corresponding entities in the conversation history.” Here, since every mention-entity pair is computed for similarity, those that fall below the threshold and are not related can be considered the one or more third embeddings),
wherein the determining that the first entity is related to the second entity occurs based at least on the first entity not being related to the one or more third entities (Joko, page 7, col 1, ¶4 “For every mpe, we compute this similarity with all the previously linked entities in the conversation and find the most similar entity. Mention-entity pairs 〈mpe, e〉 below a certain threshold τ are ignored. This threshold allows for filtering personal entity mentions that do not have the corresponding entities in the conversation history.” Here, the most similar entity can be considered the second entity, and all other entities can be considered the one or more third entities. By determining the most similar entity, the first entity is not related to all other entities).
Regarding claim 6:
Joko in view of Mandel teaches The method of claim 5, wherein:
the one or more third entities are associated with a first entity category (Mandel, col 6, lines 21-25 “If, for example, the text data corresponds to “what is the weather,” the dialog manager 260 may determine that that the system(s) 120 is to output weather information associated with a geographic location of the device 110 a. In another example, if the text data corresponds to “turn off the lights,” the dialog manager 260 may determine that the system(s) 120 is to turn off lights associated with the device(s) 110 a or the user(s) 5.” Here, the weather or lights can be considered the category in light of the specification, ¶18 “In such an example, the food category entities may be associated with specific entities, such as the food names entity being associated with a burger entity, a pizza entity, and a salad entity.”);
the one or more second entities are associated with a second entity category that is related to the first entity category (Mandel, col 6, lines 17-21 “The dialog manager 260 determines a goal corresponding to an action that a user desires be performed as well as pieces of the text data that allow a device (e.g., the device 110, a the system(s) 120, a skill 290, a skill system(s) 225, etc.) to execute the intent” here, the device can be considered a second entity category related to the first entity category (lights)), and
the determining that the first entity is related to the second entity further occurs based at least on the second entity category being related to the first entity category (Mandel, col 6, lines 25-28 “In another example, if the text data corresponds to “turn off the lights,” the dialog manager 260 may determine that the system(s) 120 is to turn off lights associated with the device(s) 110 a or the user(s) 5.” Here, the lights associated with the user can be considered the second entity related to the entity category).
Joko and Mandel are analogous art because both references concern methods for entity linking in conversational systems. Accordingly, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to modify Joko’s conversational entity linking system to incorporate the categories taught by Mandel. The motivation for doing so would have been to process and perform tasks based on commands as stated in Mandel, col 1, lines 8-12 “Speech-recognition processing combined with natural-language understanding processing enables voice-based control of a computing device to perform tasks based on the user's spoken commands.”
Regarding claim 9:
Joko in view of Mandel teaches The method of claim 1, wherein:
the determining the at least the first entity associated with the request uses one or more first machine learning models of the one or more machine learning models (Mandel, col 8, lines 34-42 “An entity chunker 312 may be used to determine that the input text data 302 includes a representation of one or more entities, a process that may include named entity recognition (NER)—i.e., determining that the input text data 302 includes the representation—and entity resolution (ER)—i.e., identifying a meaning or context of the entity, such as associating an identity of a person based on a recognized nickname.” Here, the entity chunker can be considered the first machine learning model); and
the determining the first embedding associated with the first entity uses one or more second machine learning models of the one or more machine learning models (Mandel, col 18, lines 7-10 “The encoder 1202 may be implemented as a recurrent neural network (RNN) using, for example, LSTM cells, and may further use dense layers, embedding layers, or any other such layers.” Here, the RNN using LSTM can be considered the second machine learning model).
Joko and Mandel are analogous art because both references concern methods for entity linking in conversational systems. Accordingly, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to modify Joko’s conversational entity linking system to incorporate the multiple models taught by Mandel. The motivation for doing so would have been to process and perform tasks based on commands as stated in Mandel, col 1, lines 8-12 “Speech-recognition processing combined with natural-language understanding processing enables voice-based control of a computing device to perform tasks based on the user's spoken commands.”
Regarding claim 10:
Joko in view of Mandel teaches The method of claim 1, wherein one of:
the response includes at least a first word associated with the second entity; or the response includes at least a second word associated with a third entity that is related to the second entity (Mandel, col 13, lines 22-25 “Further continuing the example above, the NLG system may select a template in response to the question, “What is the weather currently like?” of the form: “The weather currently is $weather_information$.”” It is noted the claim recites alternative language, and Mandel teaches at least one of the alternatives.).
It would have been obvious to combine the teachings of Joko and Mandel for the reasons set forth in connection with claim 1 above.
Regarding claim 11:
Joko teaches A system comprising:
determine, using one or more machine learning models and based at least on first data…, at least a first entity associated with the request (Joko, page 7, col 2, section 6, ¶1 “In this paper, we studied entity linking in a broad setting of conversational systems: QA, task-oriented, and social chat.” Further, Joko, page 3, col 1, ¶1 “These cover the three main categories of conversational problems [30]: question answering (QA), task-oriented systems, and social chat (cf. Sect. 3).” Here, the entity linked in a question answering (QA) problem can be considered a request);
determine, using the one or more machine learning models, a first embedding associated with the first entity (Joko, page 5, col 2, section 4.2, ¶1 “Once this mapping was done, mention-entity pairs can be identified as described in Stage 1 of Section 4.1.” here, the mapped mention-entity pairs can be considered the embedding);
determine, based at least on a latent space comparison between the first embedding and one or more second embeddings associated with one or more of second entities, that the first entity is related to a second entity of the one or more second entities (Joko, page 7, col 1, ¶4 “Considering a personal entity mention mpe , and an entity e, the PE method computes the cosine similarity between the word embedding of mpe and the entity embedding of entity e. For every mpe, we compute this similarity with all the previously linked entities in the conversation and find the most similar entity.” Here, the first entity can be considered related to the second entity if it is the most similar entity and further, Specification, ¶42 “For instance, in some examples, the association component 118 may perform cosine similarity to determine cosine similarity values between the embedding associated with the entity and the embeddings associated with the stored entities.”);
Joko does not teach "one or more processing units to:
…representative of a request
generate, based at least on at least one of the first entity or the second entity, second data representative of a response to the request."
However, Mandel teaches one or more processing units (Mandel, claim 12 “at least one processor;”) to:
…representative of a request (Mandel, col 13, lines 22-25 “Further continuing the example above, the NLG system may select a template in response to the question, “What is the weather currently like?” of the form: “The weather currently is $weather_information$.”” Here, the question regarding the weather can be considered the request)
generate, based at least on at least one of the first entity or the second entity, second data representative of a response to the request (Mandel, col 13, lines 22-25 “Further continuing the example above, the NLG system may select a template in response to the question, “What is the weather currently like?” of the form: “The weather currently is $weather_information$.””).
Joko and Mandel are analogous art because both references concern methods for entity linking in conversational systems. Accordingly, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to modify Joko’s conversational entity linking system to incorporate the request and response taught by Mandel. The motivation for doing so would have been to process and perform tasks based on commands as stated in Mandel, col 1, lines 8-12 “Speech-recognition processing combined with natural-language understanding processing enables voice-based control of a computing device to perform tasks based on the user's spoken commands.”
Regarding claims 12-15:
Claims 12-15 are rejected under the same rationale as claims 2-5, respectively.
Regarding claim 16:
Joko in view of Mandel teaches The system of claim 11, wherein the one or more processing units are further to one of:
generate the second data representative of the response by at least inputting the at least one of the first entity or the second entity into one or more slots of a template associated with the response (Unger, page 3, col 2, ¶1 “The query templates contain slots, which are missing elements of the query that have to be filled with URIs” further Unger, page 3, col 2, ¶1 “In a next step, sophisticated entity identification approaches are used to obtain URIs for those natural language expressions.”); or generate, using one or more second machine learning models and based at least on the first data representative of the request, the first entity, and the second entity, the second data representative of the response to the request (It is noted the claim recites alternative language, and Unger teaches at least one of the alternatives.).
Regarding claim 17:
Claim 17 is rejected under the same rationale as claim 9.
Regarding claim 18:
Joko in view of Mandel teaches The system of claim 11, wherein the system is comprised in at least one of:
a control system for an autonomous or semi-autonomous machine; a perception system for an autonomous or semi-autonomous machine; a system for performing simulation operations; a system for performing digital twin operations; a system for performing light transport simulation; a system for performing collaborative content creation for 3D assets; a system for performing deep learning operations; a system implemented using an edge device; a system implemented using a robot; a system for performing conversational AI operations (Joko, page 1, col 2, ¶1 “Conversational systems are becoming increasingly important with the proliferation of personal assistants, such as Siri, Alexa, Cortana, and the Google Assistant.”); a system implementing one or more large language models (LLMs); a system for generating synthetic data; a system incorporating one or more virtual machines (VMs); a system implemented at least partially in a data center; or a system implemented at least partially using cloud computing resources (It is noted the claim recites alternative language, and Joko teaches at least one of the alternatives.).
Regarding claim 19:
Joko teaches A processor comprising:
wherein the response is generated based at least on a first entity included in the request (Joko, page 7, col 2, section 6, ¶1 “In this paper, we studied entity linking in a broad setting of conversational systems: QA, task-oriented, and social chat.” Further, Joko, page 3, col 1, ¶1 “These cover the three main categories of conversational problems [30]: question answering (QA), task-oriented systems, and social chat (cf. Sect. 3).” Here, the entity linked in a question answering (QA) problem can be considered a request) and a second entity that is related to the first entity, the first entity being related to the second entity based at least on a first embedding associated with the first entity and a second embedding associated with the second entity (Joko, page 7, col 1, ¶4 “Considering a personal entity mention mpe , and an entity e, the PE method computes the cosine similarity between the word embedding of mpe and the entity embedding of entity e. For every mpe, we compute this similarity with all the previously linked entities in the conversation and find the most similar entity.” Here, the first entity can be considered related to the second entity if it is the most similar entity and further, Specification, ¶42 “For instance, in some examples, the association component 118 may perform cosine similarity to determine cosine similarity values between the embedding associated with the entity and the embeddings associated with the stored entities.”).
Joko does not teach "one or more processing units to generate first data representative of a response associated with a request"
However, Mandel teaches one or more processing units (Mandel, claim 12 “at least one processor;”) to generate first data representative of a response associated with a request (Mandel, col 13, lines 22-25 “Further continuing the example above, the NLG system may select a template in response to the question, “What is the weather currently like?” of the form: “The weather currently is $weather_information$.”” Here, the question regarding the weather can be considered the request)
Joko and Mandel are analogous art because both references concern methods for entity linking in conversational systems. Accordingly, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to modify Joko’s conversational entity linking system to incorporate the request and response taught by Mandel. The motivation for doing so would have been to process and perform tasks based on commands as stated in Mandel, col 1, lines 8-12 “Speech-recognition processing combined with natural-language understanding processing enables voice-based control of a computing device to perform tasks based on the user's spoken commands.”
Regarding claim 20:
Claim 20 is rejected under the same rationale as claim 18.
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over Joko in view of Mandel in further view of Unger et al. ("Template-based question answering over RDF data", Unger et al., 16 April 2012) hereinafter Unger.
Regarding claim 7:
Joko in view of Mandel teaches The method of claim 1,
Joko in view of Mandel does not teach "wherein the generating the second data representative of the response to the request comprises:
receiving a template associated with the response, the template including at least one or more words and one or more slots associated with inputting one or more entities; and
generating the second data representative of the response by inputting the at least one of the first entity or the second entity into the one or more slots."
However, Unger teaches wherein the generating the second data representative of the response to the request comprises:
receiving a template associated with the response, the template including at least one or more words and one or more slots associated with inputting one or more entities (Unger, page 3, col 2, ¶1 “The query templates contain slots, which are missing elements of the query that have to be filled with URIs”); and
generating the second data representative of the response by inputting the at least one of the first entity or the second entity into the one or more slots (Unger, page 3, col 2, ¶1 “The query templates contain slots, which are missing elements of the query that have to be filled with URIs” further Unger, page 3, col 2, ¶1 “In a next step, sophisticated entity identification approaches are used to obtain URIs for those natural language expressions.”).
Joko in view of Mandel and Unger are analogous art because both references concern methods for entity linking. Accordingly, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to modify Joko/Mandel’s entity linking system to incorporate the text templates taught by Unger. The motivation for doing so would have been to answer questions that could not be answered with other approaches, as stated in Mandel, page 2, abstract, ¶1 “To circumvent this problem, we present a novel approach that relies on a parse of the question to produce a SPARQL template that directly mirrors the internal structure of the question. This template is then instantiated using statistical entity identification and predicate detection. We show that this approach is competitive and discuss cases of questions that can be answered with our approach but not with competing approaches.”
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Joko in view of Mandel in further view of Vos et al. ("Towards Parameter-Efficient Automation of Data Wrangling Tasks with Prefix-Tuning", Vos et al., 2022) hereinafter Vos.
Regarding claim 8:
Joko in view of Mandel teaches The method of claim 1,
Joko in view of Mandel does not teach "wherein the generating the second data representative of the response to the request comprises generating, using one or more large language models (LLMs) and based at least on the first data representative of the request, the first entity, and the second entity, the second data representative of the response to the request"
However, Vos teaches wherein the generating the second data representative of the response to the request comprises generating, using one or more large language models (LLMs) and based at least on the first data representative of the request, the first entity, and the second entity, the second data representative of the response to the request (Vos, page 1, section 1, ¶2 “A concrete example for data wrangling is to generate a prompt that asks an LLM to perform entity matching, e.g.: Product A is Title: Macbook Pro Price: $1,999, Product B is Title: Macbook Air Price: $899. Are product A and product B the same?. The output is evaluated by checking whether the LLM generates Yes or No as a response [14].”).
Joko in view of Mandel and Vos are analogous art because both references concern methods for entity linking. Accordingly, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to modify Joko/Mandel’s entity linking system to incorporate the LLM taught by Vos. The motivation for doing so would have been to achieve state-of-the-art performance on data “Narayan et al. showed that LLMs can achieve state-of-the-art performance on data wrangling tasks when manually tuned with a simple transfer learning technique called prompting [14].”.
Conclusion
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/J.S.M./Examiner, Art Unit 2122
/KAKALI CHAKI/Supervisory Patent Examiner, Art Unit 2122