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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.
Applicant's submission filed on 08/20/2026 has been entered. Claims 1, 8 & 15 were amended. Claims 1-20 are pending.
Power of Attorney Request by Examiner
The examiner notes a Power of Attorney appointing registered practitioners has not been filed in this application to date, and requests that one be filed as soon as possible.
Internet Communications Authorization Request by Examiner
In addition to a Power of Attorney being filed, the examiner requests that a Form 439, which provides MPEP § 502.03 authorization, be filed by Applicant’s representative. This will facilitate future communications with the examiner as prosecution continues.
Response to Arguments
Applicant's arguments with respect to the § 103 rejections have been fully considered but they are not persuasive.
Applicant argues that the cited references “do not convert the semi-final answer back into a graph and compare the semi-final answer graph to the produced ‘ground truth’ graph as recited by claims 1, 8 & 15 as amended. This validation process is therefore not taught by the cited references.” The examiner respectfully disagrees.
First, it is noted that the features upon which applicant relies (i.e., graphs) are not recited in the rejected claims. Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993). Claims 2, 9 & 16 continue to teach these limitations as the claims are presented.
Second, Applicant’s amendments to the independent claims (i.e., claims 1, 8 & 15) incorporated limitations from dependent claims 2, 9 & 16, respectively, without deleting those limitations from the original claims. A § 112(d) rejection appears below, and the antecedent basis of the entire claims set should be adjusted based on the corrected form of the independent claims.
Claim Rejections - 35 USC § 112(d)
The following is a quotation of 35 U.S.C. 112(d):
(d) REFERENCE IN DEPENDENT FORMS.—Subject to subsection (e), a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
The following is a quotation of pre-AIA 35 U.S.C. 112, fourth paragraph:
Subject to the following paragraph [i.e., the fifth paragraph of pre-AIA 35 U.S.C. 112], a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
Claims 2, 9 & 16 are rejected under 35 U.S.C. 112(d) or pre-AIA 35 U.S.C. 112, 4th paragraph, as being of improper dependent form for failing to further limit the subject matter of the claim upon which it depends, or for failing to include all the limitations of the claim upon which it depends.
Applicant’s 08/20/2026 amendments to the independent claims (i.e., claims 1, 8 & 15) incorporated limitations from dependent claims 2, 9 & 16, respectively, without deleting those limitations from the original claims.
Applicant may cancel the claim(s), amend the claim(s) to place the claim(s) in proper dependent form, rewrite the claim(s) in independent form, or present a sufficient showing that the dependent claim(s) complies with the statutory requirements.
Examiner’s Note
Claim 15 recites “A computer program product, comprising: a set of one or more computer-readable storage media”. Specification paragraph [0102] describes, in part:
[0102] In these illustrative examples, computer-readable storage media 624 is a physical or tangible storage device used to store program code 618 rather than a medium that propagates or transmits program code 618. Computer-readable storage media 624, as used herein, is not to be construed as being transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission media (e.g., light pulses passing through a fiber-optic cable), or electrical signals transmitted through a wire. . . .
(Emphasis added).
Therefore, claims 15-20 are understood to not be directed towards propagating signals.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
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 1-5, 7-12, 14-18 & 20 are rejected under 35 U.S.C. 103 as being unpatentable over:
(i) “Enhancing Knowledge Graph Construction Using Large Language Models” by Trajanoska et al. (published May 2023, hereinafter “Trajanoska”) in view of
(ii) “Retrieval-Augmented Generation with Knowledge Graphs for Customer Service Question Answering” by Xu et al. (published July 2024, hereinafter “Xu”).
Trajanoska teaches:
1. A computer implemented method comprising:
creating, by a processor set, a first large language model for generating symbolic knowledge representations based on a set of data received from multi-modal documents from a plurality of data sources [Trajanoska, page 2, § II.A, paragraph spanning both columns and the following paragraph];
generating, by the processor set, a number of symbolic knowledge representations based on the set of data, wherein each node in the number of symbolic knowledge representations represents a concept and each edge in the number of symbolic knowledge representations represents a relationship between concepts [Trajanoska, page 4, Fig. 2 and § IV.B].
Trajanoska does not explicitly teach, but Xu does teach:
receiving, by the processor set, a query comprising textual information received through a user-input from a user [Xu, page 2907, § 3.2.1];
filtering, by the processor set, the number of symbolic knowledge representations to identify a portion of symbolic knowledge representation based on the textual information in the query [Xu, pages 2907 & 2908, § 3.2.2];
generating, by the processor set using a second large language model, a response based on the portion of symbolic knowledge representation [Xu, pages 2907 & 2908, § 3.2.2];
validating, by the processor set, the response using the portion of symbolic knowledge representation [Xu, pages 2907 & 2908, § 3.2.2] including:
generating, by the processor set using the first large language model, a symbolic knowledge representation using the response [Xu, pages 2907 & 2908, § 3.2.2]; and
comparing, by the processor set, the symbolic knowledge representation with the portion of symbolic knowledge representation [Xu, pages 2907 & 2908, § 3.2.2]; and
returning, by the processor set, the response to the user based on the validation [Xu, page 2908, § 3.2.3].
Trajanoska and Xu are analogous art because they are in the same field of endeavor, knowledge graphs and large language models. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teaching of the cited references and further modify Trajanoska by Xu because combining retrieval-augmented generation prompt answering with a built knowledge graph allows for domain-specific query responses and increases the likelihood of better matching results.
The combination of Trajanoska and Xu teaches:
2. The computer implemented method of claim 1, wherein validating, by the processor set, the response using the portion of symbolic knowledge representation comprises:
generating, by the processor set using the first large language model, a symbolic knowledge representation using the response [Xu, pages 2907 & 2908, § 3.2.2];
comparing, by the processor set, the symbolic knowledge representation with the portion of symbolic knowledge representation to generate a similarity score [Xu, pages 2907 & 2908, § 3.2.2]; and
in response to determining that the similarity score exceeds a pre-defined threshold, validating, by the processor set, the response generated for the query [Xu, pages 2907 & 2908, § 3.2.2].
3. The computer implemented method of claim 1, wherein creating, by a processor set, a first large language model for generating symbolic knowledge representations based on a set of data received from multi-modal documents from a plurality of data sources comprises:
finetuning, by the processor set, the first large language model by utilizing existing datasets of knowledges and schemas of prompts for generating the number of symbolic knowledge representations [Trajanoska, page 2, § II.A, paragraph spanning both columns and the following paragraph]; and
validating, by the processor set, the first large language model using a number of benchmark symbolic knowledge representations generated by humans [Trajanoska, page 2, § II.A, paragraph spanning both columns and the following paragraph].
4. The computer implemented method of claim 1, wherein the portion of symbolic knowledge representation is generated by performing filtering based on spatiotemporal information from the textual information in the query [Xu, page 2907, § 3.2.1].
5. The computer implemented method of claim 1, wherein the set of data received from a plurality of data sources comprises sensor data [Trajanoska, page 2, § II.B].
7. The computer implemented method of claim 1, wherein the first large language model incorporates multi-modal language models (MLLMs) for processing the set of data [Trajanoska, page 2, § II.A, paragraph spanning both columns and the following paragraph].
Claims 8-12 & 14 recite limitations corresponding to those recited in claims 1-5 & 7, respectively, and are rejected for the same reasons discussed above.
Claims 15-18 & 20 recite limitations corresponding to those recited in claims 1-4 & 7, respectively, and are rejected for the same reasons discussed above.
Claims 6, 13 & 19 are rejected under 35 U.S.C. 103 as being unpatentable over:
(i) Trajanoska in view of
(ii) Xu, and further in view of
(iii) “Evidence-Driven Retrieval Augmented Response Generation for Online Misinformation” by Yue et al. (published May 2024, hereinafter “Yue”).
The combination of Trajanoska and Xu does not explicitly teach, but Yue teaches:
6. The computer implemented method of claim 1, wherein the response is validated by detecting misinformation and disinformation in the response based on deductive reasoning or approximate deductive reasoning for the response [Yue, page 8, § 4.3].
Trajanoska, Xu, and Yue are analogous art because they are in the same field of endeavor, knowledge graphs and large language models. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teaching of the cited references and further modify Trajanoska and Xu by Yue because combining retrieval-augmented generation prompt answering with reinforcement learning allows for improving response quality and decreasing misinformation and disinformation by optimizing the algorithm’s reward.
Claims 13 & 19 recite limitations corresponding to those recited in claim 6, respectively, and are rejected for the same reasons discussed above.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Scott A. Waldron whose telephone number is (571)272-5898. The examiner can normally be reached Monday - Friday 9:00 am - 5:00 pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Ajay Bhatia can be reached at (571) 272-3906. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/Scott A. Waldron/Primary Examiner, Art Unit 2156
Prosecution Insights