Prosecution Insights
Last updated: April 18, 2026
Application No. 18/148,431

LABELED KNOWLEDGE GRAPH BASED PRIMING OF A NATURAL LANGUAGE MODEL PROVIDING USER ACCESS TO PROGRAMMATIC FUNCTIONALITY THROUGH NATURAL LANGUAGE INPUT

Final Rejection §103
Filed
Dec 29, 2022
Examiner
PHAM, THIERRY L
Art Unit
2654
Tech Center
2600 — Communications
Assignee
Microsoft Technology Licensing, LLC
OA Round
2 (Final)
81%
Grant Probability
Favorable
3-4
OA Rounds
2y 9m
To Grant
85%
With Interview

Examiner Intelligence

Grants 81% — above average
81%
Career Allow Rate
569 granted / 705 resolved
+18.7% vs TC avg
Minimal +5% lift
Without
With
+4.7%
Interview Lift
resolved cases with interview
Typical timeline
2y 9m
Avg Prosecution
12 currently pending
Career history
717
Total Applications
across all art units

Statute-Specific Performance

§101
11.7%
-28.3% vs TC avg
§103
40.0%
+0.0% vs TC avg
§102
29.4%
-10.6% vs TC avg
§112
8.2%
-31.8% vs TC avg
Black line = Tech Center average estimate • Based on career data from 705 resolved cases

Office Action

§103
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 following communication: an amendment filed on 1/14/2026. ● Claims 2-21 are currently pending; claim 1 has been canceled. 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. Claim(s) 2-21 are rejected under 35 U.S.C. 103 as being unpatentable over Singaraju et al (US 20200057946) in view of Reschke et al (US 20180121500). Regarding claim 2, Singaraju discloses a computer-implemented method comprising: receiving a natural language input (input utterance, pars. 9-10); comparing the natural language input with natural language input examples (comparing/analyzing input utterance with matching keywords/phrases, pars. 138-139), wherein the natural language input includes concatenated natural language words or phrases of multiple labels from the labeled knowledge graph; wherein the natural language input examples include concatenated natural language words or phrases (concatenated words/phrases samples, pars. 71-76) of multiple labels from a labeled knowledge graph of an application program; based on the comparing, determining that the natural language input is for a function (functions of application program, pars. 150-152) provided by the application program; and based on the determining, invoking (par. 178) the function provided by the application program (pars. 28-32). Singaraju fails to teach and/or suggest parsing (pars. 16, 41, and 63) a knowledge graph of an application program. Reschke, in the same field of endeavor for natural language processing, teaches a method of parsing a knowledge graph of an application and generating natural language input samples. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention by modifying natural language processing of Singaraju to include a method of parsing a knowledge graph of an application and generating natural language input samples as taught by Reschke because it offers several transformative advantages over traditional flat data or keyword-based systems. Therefore, it would have been obvious to combine Sangaraju with Reschke to obtain the invention as specified in claim 1. Regarding claim 3, Singaraju further discloses the computer-implemented method of claim 2, wherein the comparing is performed using a pre-trained language model (pre-trained language model, pars. 143-146) that analyzes the natural language input. Regarding claim 4, Singaraju further discloses the computer-implemented method of claim 2, wherein the labeled knowledge graph comprises nodes and links, wherein the nodes and the links (links/nodes, pars. 105, 121, 122) between the nodes in the labeled knowledge graph are labeled with a natural language word or phrase, and wherein parsing the labeled knowledge graph includes identifying the nodes and the links between the nodes. Regarding claim 5, Singaraju further discloses the computer-implemented method of claim 2, wherein the concatenated natural language words or phrases include a word or phrase (pars. 73-76) used to label a link appended to an end of a word or phrase used to label a preceding node (pars. 101, 105). Regarding claim 6, Singaraju further discloses the computer-implemented method of claim 2, wherein the concatenated natural language words or phrases include a word or phrase used to label a link (pars. 4-8) prepended to a beginning of a word or phrase used to label a preceding node (pars. 101. 105). Regarding claim 7, Singaraju further discloses the computer-implemented method of claim 2, wherein each of the natural language input examples corresponds to a functionality (functionality of application program, pars. 150-152) provided by the application program. Regarding claim 8, Singaraju further discloses the computer-implemented method of claim 2, wherein the comparing further comprises: determining one of the natural language input examples that is most similar (pars. 74-77) or closest to the natural language input; providing a correspondence (par. 133) between the one of the natural language input examples and the labeled knowledge graph (labeled knowledge graph, pars. 133-135) of the application program; and based upon the correspondence, identifying a provided by the application program. Regarding claims 9-21 recite limitations that are similar and in the same scope of invention as to those in claims 2-8 above; therefore, claims 9-21 are rejected for the same rejection rationale/basis as described in claims 2-8. Response to Arguments ● Applicant’s arguments with respect to claim(s) 2-21 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument. ● Applicant’s arguments, see pages 7-10, filed 1/14/2026, with respect to claims 2-21 have been fully considered and are persuasive. The 35 U.S.C. 101 rejection (abstract idea) of said claims has been withdrawn. Conclusion Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a). A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action. Any inquiry concerning this communication or earlier communications from the examiner should be directed to THIERRY L PHAM whose telephone number is (571)272-7439. The examiner can normally be reached M-F, 11-6. 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, Hai Phan can be reached at 571-272-6338. 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. /THIERRY L PHAM/Primary Examiner, Art Unit 2654
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Prosecution Timeline

Dec 29, 2022
Application Filed
Oct 15, 2025
Non-Final Rejection — §103
Dec 01, 2025
Interview Requested
Dec 11, 2025
Applicant Interview (Telephonic)
Dec 12, 2025
Examiner Interview Summary
Jan 14, 2026
Response Filed
Apr 07, 2026
Final Rejection — §103 (current)

Precedent Cases

Applications granted by this same examiner with similar technology

Patent 12586585
SPEECH RECOGNITION APPARATUS, CONTROL METHOD, AND NON-TRANSITORY STORAGE MEDIUM
2y 5m to grant Granted Mar 24, 2026
Patent 12585891
NATURAL LANGUAGE GENERATION USING KNOWLEDGE GRAPH INCORPORATING TEXTUAL SUMMARIES
2y 5m to grant Granted Mar 24, 2026
Patent 12579376
LABEL PROPAGATION USING CONTRASTIVE LEARNING PROJECTIONS
2y 5m to grant Granted Mar 17, 2026
Patent 12554941
PROCESSING EVENT DATA AND/OR TABULAR DATA FOR INPUT TO ONE OR MORE MACHINE LEARNING MODELS
2y 5m to grant Granted Feb 17, 2026
Patent 12547648
LANGUAGE MODEL DECODING FOR SEARCH QUERY COMPLETION
2y 5m to grant Granted Feb 10, 2026
Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

3-4
Expected OA Rounds
81%
Grant Probability
85%
With Interview (+4.7%)
2y 9m
Median Time to Grant
Moderate
PTA Risk
Based on 705 resolved cases by this examiner. Grant probability derived from career allow rate.

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