Prosecution Insights
Last updated: October 23, 2026
Application No. 19/082,558

GENERATIVE ARTIFICIAL INTELLIGENCE ROBUSTNESS TO UNSTRUCTURED PROMPTS

Final Rejection §101
Filed
Mar 18, 2025
Examiner
ORTIZ DITREN, BELIX M
Art Unit
2164
Tech Center
2100 — Computer Architecture & Software
Assignee
International Business Machines Corporation
OA Round
2 (Final)
84%
Grant Probability
Favorable
3-4
OA Rounds
1y 3m
Est. Remaining
87%
With Interview

Examiner Intelligence

Grants 84% — above average
84%
Career Allowance Rate
587 granted / 698 resolved
+29.1% vs TC avg
Minimal +3% lift
Without
With
+2.6%
Interview Lift
resolved cases with interview
Typical timeline
2y 10m
Avg Prosecution
8 currently pending
Career history
719
Total Applications
across all art units

Statute-Specific Performance

§101
15.1%
-24.9% vs TC avg
§103
41.7%
+1.7% vs TC avg
§102
23.2%
-16.8% vs TC avg
§112
10.1%
-29.9% vs TC avg
Black line = Tech Center average estimate • Based on career data from 698 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 . Remarks In response to communication files on June 18, 2025, claims 1, 6- 8, 13-15, and 20 are amended and claims 4-5, 11-12, and 18-19 are cancelled by applicant's request. Therefore, claims 1-3, 6-10, 13-17, and 20 are presently pending in the application. 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, 6-10, 13-17, and 20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Regarding claims 1, 8, and 15, Step 1 Analysis: Claims 1, 8, and 15 are directed to a process, a system and a medium, which falls within one of the four statutory categories. Step 2A Prong 1 Analysis: Claims 1, 8, and 15 recites, The limitations of: “generating a respective associated response to each user prompt of the set” is a mental process which can be performed by the human mind. A human can generate a response to a user prompt. “determining a user-approved, associated response to a final user prompt of the set” is a mental process which can be performed by the human mind. A human can compare different responses to make a determination. “defining a respective tuple mapping for each user prompt of the set to the user-approved, associated response” is a mental process which can be performed by the human mind. A human can set tuple mappings between sets of responses. “extracting one or more topic-related keywords from the final user prompt, wherein the one or more topic-related keywords are extracted by applying, “generating an internal prompt representation of the final user prompt using a topic-guided reverse prompt, wherein the topic-guided reverse prompt is generated, “generating an associated response to the internal prompt representation” is a mental process and can be performed by the human mind. A human can come up with a response to a prompt. “defining respective tuple mappings for the internal prompt representation to the user- approved, associated response and to the associated response” and “defining a respective tuple mapping for each user prompt of the set to the associated response” are mental process can be performed by the human mind. A human can set tuple mappings between sets of responses. Step 2A prong 2, Claims 1, 8 and 15 recited the following additional elements: “receiving a set of user prompts to a large language model (LLM)”, “the LLM”, and “fine-tuning the LLM based on defined tuple mappings”. The limitation of “receiving” is an additional element and is insignificant extra-solution activity as retrieval/receiving of data (i.e. mere data gathering) such as 'obtaining information' as identified in MPEP 2106.05(g) and does not provide integration into a practical application. The recited “the LLM” is a nominal recitation of a model used to apply the exception. Thus, these additional elements that do not do more than recite the words "apply it" (or an equivalent) and do not integrate a judicial exception into a practical application. Furthermore the limitation “fine-tuning the LLM based on defined tuple mappings” also do not do more than recite the words “apply it” or (an equivalent) and do not integrate a judicial exception into a practical application. In addition Claim 8 recites processors, memories and claims 8 and 15 recite computer readable storage medium, note that these recited additional elements are a high-level recitation of generic computer components to perform the mental process and applied on a computer as in MPEP 2106.05(f), which does not provide integration into a practical application. Step 2B: the conclusions for the additional elements representing mere implementation using a computer are carried over and do not provide significantly more. With respect to the "receiving” limitation is identified as insignificant extra-solution activity above when re-evaluated this element is well-understood, routine, and conventional as evidenced by the court cases in MPEP 2106.05(d)(II), "i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); … OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network);" and thus remains insignificant extra-solution activity that does not provide significantly more. Furthermore, the limitations “the LLM and fine-tuning the LLM based on defined tuple mappings” are generally linking the use of the judicial exception to a particular technological environment or field of use, MPEP 2106.05(h). Lastly the recitation of “processor” and “memory” and computer readable storage medium are recitation of generic computer components to perform the mental process and applied on a computer as in MPEP 2106.05(f). Therefore, the claims as a whole does not change this conclusion and the claims are ineligible. Claims 2-3, 6-7, 9-10, 13-14, 16-17, and 20, the rejection of claim 1 is further incorporated, and further, the claim recites: determining user approval…, …, selecting a version…, etc. further describes the abstract idea previously identified in the independent claims, Thus, the claims recite an abstract idea and are not eligible. Response to Arguments Applicant's arguments filed on June 18, 2026, with respect to the rejected claims in view of the 101 rejection have been fully considered but they are not persuasive: In response to applicants’ arguments to the 101 rejection, the claim is a generic LLM fine-tuning workflow without any specific technical improvement to computer functionality. These are all data processing steps performed by a generic LLM making it a mental process. There is no specific algorithm, no new model architecture, and no improvement to computer functionality. Thus, under Alice Step 1, the claim is directed to an abstract idea. Allowable Subject Matter Claims 1-3, 6-10, 13-17, and 20 are allowed. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to BELIX M ORTIZ DITREN whose telephone number is (571)272-4081. The examiner can normally be reached M-F 9am -5pm. 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, Amy Ng can be reached at 571-270-1698. 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. BELIX M. ORTIZ DITREN Primary Examiner Art Unit 2164 /Belix M Ortiz Ditren/Primary Examiner, Art Unit 2164
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Prosecution Timeline

Mar 18, 2025
Application Filed
Apr 01, 2026
Non-Final Rejection mailed — §101
Jun 10, 2026
Interview Requested
Jun 18, 2026
Applicant Interview (Telephonic)
Jun 18, 2026
Response Filed
Jun 26, 2026
Examiner Interview Summary
Sep 29, 2026
Final Rejection mailed — §101 (current)

Precedent Cases

Applications granted by this same examiner with similar technology

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1y 10m to grant Granted Sep 01, 2026
Patent 12699675
MANAGED FOLDERS
2y 4m to grant Granted Aug 04, 2026
Patent 12699700
PROCESSING A SUBSET OF A FEATURE SET TO DETERMINE WHETHER TO PROCESS A QUERY REQUEST ON A LOCAL ARTIFICIAL INTELLIGENCE ENGINE OR A REMOTE ARTIFICIAL INTELLIGENCE ENGINE
2y 2m to grant Granted Aug 04, 2026
Patent 12694310
URGENCY DRIVEN DYNAMIC EXPLAINABILITY
4y 7m to grant Granted Jul 28, 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
84%
Grant Probability
87%
With Interview (+2.6%)
2y 10m (~1y 3m remaining)
Median Time to Grant
Moderate
PTA Risk
Based on 698 resolved cases by this examiner. Grant probability derived from career allowance rate.

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