Prosecution Insights
Last updated: April 19, 2026
Application No. 17/452,609

AUTOMATIC GENERATION OF QUESTION ANSWER PAIRS

Final Rejection §101
Filed
Oct 28, 2021
Examiner
NEWAY, SAMUEL G
Art Unit
2657
Tech Center
2600 — Communications
Assignee
International Business Machines Corporation
OA Round
4 (Final)
75%
Grant Probability
Favorable
5-6
OA Rounds
3y 0m
To Grant
83%
With Interview

Examiner Intelligence

Grants 75% — above average
75%
Career Allow Rate
517 granted / 686 resolved
+13.4% vs TC avg
Moderate +8% lift
Without
With
+7.6%
Interview Lift
resolved cases with interview
Typical timeline
3y 0m
Avg Prosecution
29 currently pending
Career history
715
Total Applications
across all art units

Statute-Specific Performance

§101
16.6%
-23.4% vs TC avg
§103
34.5%
-5.5% vs TC avg
§102
17.1%
-22.9% vs TC avg
§112
20.1%
-19.9% vs TC avg
Black line = Tech Center average estimate • Based on career data from 686 resolved cases

Office Action

§101
DETAILED ACTION This is responsive to the amendment filed 26 November 2025. Claims 1, 3-8, 10-15, 17-20 and 24-26 remain pending and are considered below. 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 . Response to Arguments Applicant's arguments filed 26 November 2025 have been fully considered but they are not persuasive. Regarding the 35 USC 101 rejection, Applicant argues The claim 1 includes steps and features that integrate the claimed technical advancements into a practical application. The claim 1 includes a pipeline of four machine learning models which work together to automate the generation of question- answer pairs which are then used to train a user and provide appropriate feedback to responses that the user provides to questions received during the training. Appellant's specification identifies a technical problem and explains the details of an unconventional technical solution expressed in the claim. The claimed subject matter overcomes the disadvantages and eliminates complications found in the conventional technology for automated generation and implementation of a user training program. The claimed subject matter provides a specific way to solve the technical problem instead of claiming merely the idea of a solution or outcome itself. A pipeline of four machine learning models including one that comprises a BART-based model that was trained using training data comprising questions received from users is much more than generic computer components. Applicant respectfully submits that the presently claimed invention cannot be practically performed entirely within the human mind. In particular, the use of four machine learning models to generate and use a user training system cannot be practically performed entirely within the human mind. The Examiner respectfully disagrees. The “pipeline of four machine learning models” is recited at a high-level of generality (i.e., as generic processors performing generic computer functions) such that it amounts to no more than mere instructions to apply the exception using a generic computer components. As such the pipeline does not integrate the abstract idea into a practical application. Applicant further argues: Applicant's claim 1 includes numerous details which capture a specific scope instead of seeking a monopoly over an abstract idea. Moreover, the amended claim 1 is like the claim 3 of Patent-Eligibility Subject Matter Example 47 which was said to be patent eligible. In that claim, an expert human could also detect one or more anomalies in network traffic, but using a trained ANN (instead of a human) to perform this task helps provide technical advancements to the field. Although a human expert in reading and textual analysis could perform some of the tasks that are recited in Applicant's proposed amended claim 1, using trained machine learning models provides technical advancements to the field. Using the trained machine learning models to perform these tasks could result in the task being performed in minutes which could take one or more humans days to perform, for example when the claimed method replaces manual IT operations tools with a single, intelligent, and automated IT operations platform. (See, for example, paragraph [0033] of Applicant's specification which describes this technical improvement in the field.) re integrated into a practical application. However, claim 3 of Patent-Eligibility Subject Matter Example 47 integrates the abstract idea into a practical application by dropping one or more malicious network packets in real time and blocking future traffic from a source address associated with the one or more malicious network packets. On the other hand Applicant’s claims merely apply the abstract idea using generic computer components and fail to integrate the judicial exception into a practical application. Further, the claimed methods are not rendered patent eligible by the fact that (using existing machine learning technology) they perform a task previously undertaken by humans with greater speed and efficiency than could previously be achieved. Courts have consistently held, in the context of computer-assisted methods, that such claims are not made patent eligible under § 101 simply because they speed up human activity. See, e.g., Content Extraction, 776 F.3d at 1347; DealerTrack, 674 F.3d at 1333. Whether the issue is raised at step one or step two, the increased speed and efficiency resulting from use of computers (with no improved computer techniques) do not themselves create eligibility. See, e.g., Trinity Info Media, LLC v. Covalent, Inc., 72 F.4th 1355, 1363 (Fed. Cir. 2023) (rejecting argument that “humans could not mentally engage in the ‘same claimed process’ because they could not perform ‘nanosecond comparisons’ and aggregate ‘result values with huge numbers of polls and members’”) (internal citation omitted); Customedia Techs., LLC v. Dish Network Corp., 951 F.3d 1359, 1365 (Fed. Cir. 2020) (holding claims abstract where “[t]he only improvements identified in the specification are generic speed and efficiency improvements inherent in applying the use of a computer to any task”) Applicant also argues: Moreover, proceeding arguendo that the claims are directed to an abstract idea, Applicant further respectfully submits that the claims are significantly more than the judicial exception because the claims facilitate improvement in a technological area of analyzing large amounts of information to generate useful question-answer pairs that are presented to a user for training and provide appropriate feedback to various possible user answers provided by the user during the automated training. … Thus, as the amended claim 1 results in these described improvements in this technical field and result in the generation of the user answer-specific feedback during user training, the amended claim 1 is significantly more than any judicial exception. The technical improvement requirement for the 35 U.S.C. 101 analysis does not require an improvement to a computer itself, but instead requires an improvement to a technical field. QA systems are indeed a technical field, so these enhancements for the QA systems are indeed improvements to a technical field. Applicant also reminds the Examiner that the analysis under step 2A is whether "the claim as a whole is directed to a judicial exception". Applicant here with the amended claim 1 presents a near-three hundred word claim with numerous steps and features. It is submitted that the claim as a whole is directed to a particular practical implementation and not to a monopoly on an abstract idea and not to a monopoly on an abstract idea tied to a particular computing environment. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements when considered both individually and as an ordered combination do not amount to significantly more than the abstract idea. The additional elements are recited at a high level of generality and are recited as performing generic computer functions routinely used in computer applications (see Applicant’s specification [0038], [0044], [0053] and [0083]-[0085]). Generic computer components recited as performing generic computer functions that are well-understood, routine and conventional activities amount to no more than implementing the abstract idea with a computerized system. Taken alone, the additional elements do not amount to significantly more than the above-identified judicial exception (the abstract idea). Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claims are therefore not patent eligible. All of Applicant’s arguments have been addressed and they are unpersuasive. 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, 3-8, 10-15, 17-20 and 24-26 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Further, this judicial exception is not integrated into a practical application. In claims 1, 8 and 15, the limitations receiving an input document, the input document comprising content; in response to the presenting, receiving from the user a user answer to a first one of the questions presented; matching the user answer to one of the one or more additional answers and a first answer of the questions presented; and presenting, to the user, the feedback that corresponds to the matched one of the one or more additional answers and the first answer, as drafted, are processes that, under their broadest reasonable interpretation, cover certain methods of organizing human activity (specifically managing personal behavior, relationship or interactions between people) and performance of the limitations in the mind but for the recitation of generic computer components. That is, other than reciting a “first machine learning model”, a “second machine learning model comprising a BART-based model that was trained using training data comprising questions received from users”, a “third machine learning model” and a “fourth machine learning model” (claims 1, 8 and 15), a “system … comprising: a processing unit; and a memory coupled to the processing unit, wherein the memory contains program instructions executable by the processing unit” (claim 8) and a “computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor” (claim 15) nothing in the claims precludes the steps from practically being performed in the mind. For example, a first person may receive a document from a second person, review the document to generate answers and corresponding questions to form answer-question pairs, rank the answer-question pairs by user interest and semantic correctness, select a number of highest ranked answer-question pairs, generate additional answers to the questions in the highest ranked answer-question pairs, generate feedback for the answers and the additional answers, present the questions from the highest ranked question-answer pairs to the second user, receive from the second user a user answer to one of the presented questions, match the user answer to one of the additional answers and an answer for one of the presented questions, and present to the second user the feedback that corresponds the matched user answer. If a claim limitation, under its broadest reasonable interpretation, covers managing personal behavior, relationships or interactions between people and performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Certain Methods of Organizing Human Activity” and “Mental Processes” groupings of abstract idea. Accordingly, the claims recite an abstract idea. This judicial exception is not integrated into a practical application. In particular, the claims recite the additional elements – a “first machine learning model”, a “second machine learning model comprising a BART-based model that was trained using training data comprising questions received from users”, a “third machine learning model” and a “fourth machine learning model” (claims 1, 8 and 15), a “system … comprising: a processing unit; and a memory coupled to the processing unit, wherein the memory contains program instructions executable by the processing unit” (claim 8) and a “computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor” (claim 15) which are recited at a high-level of generality (i.e., as generic processors performing generic computer functions) such that they amount to no more than mere instructions to apply the exception using a generic computer components. The claims also recite the additional elements “inputting the input document into a first machine learning model”, “inputting the input document and the answers into a second machine learning model” and “inputting the highest ranked question-answer pairs into a fourth machine learning model”. These limitations are mere nominal or tangential additions to the claim as they represent the extra-solution activities of inputting data. Accordingly, the additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claims are therefore directed to an abstract idea. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements when considered both individually and as an ordered combination do not amount to significantly more than the abstract idea. As stated above, the claims recite the additional limitations of a “first machine learning model”, a “second machine learning model comprising a BART-based model that was trained using training data comprising questions received from users”, a “third machine learning model” and a “fourth machine learning model” (claims 1, 8 and 15), a “system … comprising: a processing unit; and a memory coupled to the processing unit, wherein the memory contains program instructions executable by the processing unit” (claim 8) and a “computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor” (claim 15). However, these are recited at a high level of generality and are recited as performing generic computer functions routinely used in computer applications (see Applicant’s specification [0038], [0044], [0053] and [0083]-[0085]). Generic computer components recited as performing generic computer functions that are well-understood, routine and conventional activities amount to no more than implementing the abstract idea with a computerized system. The claims also recite the additional elements “inputting the input document into a first machine learning model”, “inputting the input document and the answers into a second machine learning model” and “inputting the highest ranked question-answer pairs into a fourth machine learning model”. These limitations represent the extra-solution activities of inputting data which are well-understood, routine and conventional activities. Thus, taken alone, the additional elements do not amount to significantly more than the above-identified judicial exception (the abstract idea). Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claims are not patent eligible. The dependent claims, when analyzed as a whole, are held to be patent ineligible under 35 U.S.C. 101 because the additional recited limitations fail to establish that the claims are not directed to an abstract idea. The dependent claims recite: receiving inputs from users; and storing the inputs into a data store; using the inputs to train the first machine learning model; parsing the input document to identify one or more semantic roles, parts of speech and named entities; wherein the first machine learning model comprises a BART based model; wherein the one or more additional answers comprise an incorrect answer to the respective question; wherein the one or more additional answers comprise an alternative correct answer to the respective question; wherein the one or more additional answers comprise an alternative correct answer to the respective question. The additional recited limitations further narrow the steps of the independent claims without however providing “a practical application of” or "significantly more than" the underlying “Mental Processes” abstract idea. Therefore, the dependent claims are also not patent eligible. Conclusion THIS ACTION IS MADE FINAL. 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 SAMUEL G NEWAY whose telephone number is (571)270-1058. The examiner can normally be reached Monday-Friday 9:00am-5:00pm EST. 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, Daniel Washburn can be reached at 571-272-5551. 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. /SAMUEL G NEWAY/Primary Examiner, Art Unit 2657
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Prosecution Timeline

Oct 28, 2021
Application Filed
Oct 04, 2023
Response after Non-Final Action
Nov 21, 2024
Non-Final Rejection — §101
Feb 18, 2025
Interview Requested
Feb 24, 2025
Applicant Interview (Telephonic)
Feb 24, 2025
Examiner Interview Summary
Feb 25, 2025
Response Filed
Apr 08, 2025
Final Rejection — §101
Jul 04, 2025
Interview Requested
Jul 14, 2025
Request for Continued Examination
Jul 18, 2025
Response after Non-Final Action
Aug 23, 2025
Non-Final Rejection — §101
Nov 18, 2025
Interview Requested
Nov 25, 2025
Examiner Interview Summary
Nov 25, 2025
Applicant Interview (Telephonic)
Nov 26, 2025
Response Filed
Jan 28, 2026
Final Rejection — §101 (current)

Precedent Cases

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

5-6
Expected OA Rounds
75%
Grant Probability
83%
With Interview (+7.6%)
3y 0m
Median Time to Grant
High
PTA Risk
Based on 686 resolved cases by this examiner. Grant probability derived from career allow rate.

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