Prosecution Insights
Last updated: October 02, 2026
Application No. 19/178,698

Generating an Output Document via an Interactive Machine-Learned Model

Final Rejection §101
Filed
Apr 14, 2025
Priority
Apr 15, 2024 — provisional 63/634,243
Examiner
HOANG, KEN
Art Unit
2168
Tech Center
2100 — Computer Architecture & Software
Assignee
Google LLC
OA Round
2 (Final)
72%
Grant Probability
Favorable
3-4
OA Rounds
1y 7m
Est. Remaining
99%
With Interview

Examiner Intelligence

Grants 72% — above average
72%
Career Allowance Rate
287 granted / 396 resolved
+17.5% vs TC avg
Strong +31% interview lift
Without
With
+31.1%
Interview Lift
resolved cases with interview
Typical timeline
3y 1m
Avg Prosecution
15 currently pending
Career history
424
Total Applications
across all art units

Statute-Specific Performance

§101
12.3%
-27.7% vs TC avg
§103
68.1%
+28.1% vs TC avg
§102
6.7%
-33.3% vs TC avg
§112
7.0%
-33.0% vs TC avg
Black line = Tech Center average estimate • Based on career data from 396 resolved cases

Office Action

§101
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 . 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 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. Examiner Notes (1) In the case of amending the Claimed invention, Applicant is respectfully requested to indicate the portion(s) of the specification which dictate(s) the structure relied on for proper interpretation and also to verify and ascertain the metes and bounds of the claimed invention. This will assist in expediting compact prosecution. MPEP 714.02 recites: “Applicant should also specifically point out the support for any amendments made to the disclosure. See MPEP § 2163.06. An amendment which does not comply with the provisions of 37 CFR 1.121 (b), (c), (d), and (h) may be held not fully responsive. See MPEP § 714.” Amendments not pointing to specific support in the disclosure may be deemed as not complying with provisions of 37 C.F.R. 1.131 (b), (c), (d), and (h) and therefore held not fully responsive. Generic statements such as "Applicants believe no new matter has been introduced" may be deemed insufficient. (2) Examiner cites particular columns, paragraphs, figures and line numbers in the references as applied to the claims below for the convenience of the applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested that, in preparing responses, the applicant fully consider the references in their entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the Examiner. Remarks Receipt of Applicant’s Amendment file on 07/27/2026 is acknowledged. Response to Arguments Applicant's arguments filed 07/27/2026 have been fully considered but they are not persuasive. Regarding 35 U.S.C. 101 rejection, applicant argues that Applicant argues that “As disclosed at paragraph [0102], an example technical benefit of the disclosure includes generating an outline and/or an output document utilizing one or more machine-learned models which generate an outline based on an initial prompt from a user and subsequently generate a plurality of questions in response to the user accepting the generated outline….. Further, the user may need to provide multiple prompts to request the one or more machine- learned models to generate the output document, and the output document generated by the computing device may be inaccurate, of poor quality, etc. Therefore, according to one or more examples of the disclosure, interactions between the user and the computing device can be reduced by the one or more machine-learned models generating answers to questions associated with the first context”, and “at paragraph [0059] it is disclosed "the one or more machine-learned models are configured to generate summaries of content, or generate new content, based on trusted source content, improving the accuracy and reliability of information and data provided to the user. Further, the one or more machine-learned models are configured to answer questions about the source content based on the trusted source content, improving the accuracy and reliability of information and data provided as answers to questions posed by the user”, and “by delineating between first and second contexts, information for generating the output document may be obtained from the appropriate source, improving the quality and accuracy of the output document” (page 9-10). Respectfully, it is noted that since the limitations regarding “machine models” does nothing to improve way of training a machine learning model that protected the model’s knowledge about previous tasks while allowing it to effectively learn new tasks; or improvements to computer component or system performance based upon adjustments to parameters of a machine learning model associated with tasks or workstreams; the steps of determining whether the generated questions can be answered by the machine models or need human to provide the answer, using the machine models, which simply “apply it” in connection with the abstract idea (mental process and/or human activities). This is not any new or improved ML models, nor any specific way of training or adjusting how the models works similar to Ex parte Desjardins. Therefore, the 35 U.S.C. 101 rejections are maintained. Claims 13 and 20 are rejected for similar reasons. 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 directed to non-statutory subject matter because it does not fall within four category of patentable subject matter recited in 35 U.S.C 101 (Process, machine manufacture or composition of matter). When considering subject matter eligibility under 35 USC 101, it must be determined whether the claim is directed to one of the four statutory categories of invention, i.e., process, machine, manufacture, or composition of matter (Step 1). If the claim does fall within one of the statutory categories, it must then be determined whether the claim is directed to a judicial exception (i.e., law of nature, natural phenomenon, and abstract idea) (Step 2A), and if so, it must additionally be determined whether the claim is a patent-eligible application of the exception. If an abstract idea is present in the claim, any element or combination of elements in the claim must be sufficient to ensure that the claim amounts to significantly more than the abstract idea itself (Step 2B). Examples of abstract ideas include fundamental economic practices; certain methods of organizing human activities; an idea itself; and mathematical relationships/formulas. Analysis: Claims 1, 13 and 20 are subject matter falls within the four statutory categories of patentable subject matter identified by 35 U.S.C. § 101: process, machine, manufacture, or composition of matter. STEP 2A, PRONG l (Claim 1): Limitation recites: (a) “receiving a first input from a user providing information including one or more source documents associated with a request to generate an output document” (b) “generating, via one or more machine-learned models, an outline of the output document based on the first input, the outline including a plurality of sections” (c) “generating, via the one or more machine-learned models, a plurality of questions for generating content for a first section among the plurality of sections, based on the first input” (d) “determining, via the one or more machine-learned models, whether a first question among the plurality of questions is associated with a first context in which the first question is identified as more appropriate for the one or more machine-learned models to answer, based on the one or more source documents or a second context in which the first question is identified as more appropriate for the user to answer, (g) “when the first question is associated with the first context, automatically retrieving, via the one or more machine-learned models, information responsive to the first question” (f) “when the first question is associated with the second context, presenting the first question to the user and obtaining, from the user, the information responsive to the first question” (g) “and generating, via the one or more machine-learned models, the content for the first section, based on the information responsive to the first question” Claim 1 recites limitations “generating,…, an outline of the output document…”(b), “generating, …, a plurality of questions for generating content…” (c), “determining,…, whether a first question among the plurality of questions is associated with a first context…” (d), “when the first question associated with the first context, automatically retrieving ….” (e), and “when the first question is associated with the second context, when the first question is associated with the second context, presenting the first question to the user and obtaining, from the user, the information responsive to the first question” (f), “generating,…, the content for the first section…”, (g) which are all steps that could be performed in the mind hence are mental processes and/or human activities. These limitations are processes that, under their broadest reasonable interpretation, covers performance of the limitation in the mind, but for the recitation of generic computer components. For example, "generating" (b) - in the context of this claim encompasses a user mentally, and with the aid of pen and paper to design the outline sections based on the user requirement and/or provided input document; “generating” (c)- human mind can form the needed inquiry for each output’s sections based on the user requirement. “determining” (d)- human mind can recognize the contextual information of the questions that something they can mentally utilize the contextual information for making judgement; “when the first question is associated with the first context, automatically retrieving…”(e)- human mind can recognize the question context and make decision accordingly; “when the first question is associated with the second context,…”(f) human mind can recognize the question context and make decision accordingly; “generating”(g) human can mentally with aid of pen and paper to form the information for each section based on the mentally retrieved information. Also, claim limitation illustrates the human activities of drafting output documents based on provided inputs. Accordingly, limitation (b-g) recites a patent-ineligible abstract idea. STEP 2A, PRONG 2 (Claim 1): The limitations “one or more memories configured to store instructions”, and “one or more processors”, which describe generic computer components, akin to adding the word "apply it" in connection with the abstract idea. Limitations recites “receiving a first input …”, “automatically retrieving…”, “…presenting the first question to the user and obtaining, from the user, the information responsive to the first question” which merely constitute insignificant solution activity (mere data gathering and output; see MPEP 2106.05(g) – presenting offers, selecting information examples); also see MPEP 2106.05(d), II.; receive/transmit over network; store/retrieve from memory/storage). Further noted, since the limitation “via one or more machine-learned models”, only akin to adding to word “apply it” in connection with the abstract idea, and does not illustrate an improved way of training a machine learning model that protected the model’s knowledge about previous tasks while allowing it to effectively learn new tasks; or improvements to computer component or system performance based upon adjustments to parameters of a machine learning model associated with tasks or workstreams; Ex Parte Desjardins, Appeal No. 2024-000567 (PTAB September 26, 2025, Appeals Review Panel Decision). This is not any new or improved Machine learning model, nor any specific way of training or adjusting how the model works similar to Ex parte Desjardins. STEP 2B (Claim 1): Under step 2B Limitations recites “receiving a first input”, “automatically retrieving…”, and “…presenting the first question to the user and obtaining, from the user, the information responsive to the first question” which merely constitute insignificant solution activity (mere data gathering and output; see MPEP 2106.05(g) – presenting offers, selecting information examples); also see MPEP 2106.05(d), II.; receive/transmit over network; store/retrieve from memory/storage) for demonstrating well understood, routine, conventional (WURC). (See Mayo, 566 U.S. at 79, 101 USPQ2d at 1968; OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015). Viewed as a whole, the additional claim elements do not provide meaningful limitations sufficient to transform the abstract idea into a patent eligible application of the abstract idea such that the claims amount to “significantly more” than the abstract idea itself. Claims 13 and 20 are rejected for similar reasons. Claims 2-12, and 14-19 are dependent on their respective parent claims and include all the limitations of the parent claims; these claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception, thus the claims are direct to abstract idea. Claims 1-20 are therefore not drawn to eligible subject matter as they are directed to an abstract idea without significantly more. 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 KEN HOANG whose telephone number is (571)272-8401. The examiner can normally be reached M-F 7:30am-5:00pm. 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, Charles Rones can be reached at (571)272-4085. 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. /KEN HOANG/Examiner, Art Unit 2168
Read full office action

Prosecution Timeline

Apr 14, 2025
Application Filed
Apr 28, 2026
Non-Final Rejection mailed — §101
Jul 06, 2026
Interview Requested
Jul 16, 2026
Applicant Interview (Telephonic)
Jul 16, 2026
Examiner Interview Summary
Jul 27, 2026
Response Filed
Aug 20, 2026
Final Rejection mailed — §101
Sep 30, 2026
Interview Requested

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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
72%
Grant Probability
99%
With Interview (+31.1%)
3y 1m (~1y 7m remaining)
Median Time to Grant
Moderate
PTA Risk
Based on 396 resolved cases by this examiner. Grant probability derived from career allowance rate.

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