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 .
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.
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 factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-2, 4, 6-14 and 16-20 are rejected under 35 U.S.C. 103(a) as being unpatentable over Ginter et al (US Pat. Pub. No. 2015/0170507) in view of Dan et al (US Pat. No. 2026/0113286).
Regarding claim 1, Ginter et al discloses a method, performed at a computer system comprising a processor and a computer-readable medium, comprising:
receiving, from a dispatch service of a plurality of dispatch services, a computer aided dispatch (CAD) message describing an event and the CAD message is in a first format, where at least some of the plurality of dispatch services generate CAD messages that are in a format other than the first format (see at least paragraphs 15 and 21 receiving emergency event message);
storing an event record that includes the structured message and the announcement text (see at least paragraph 23);
identifying user devices that are associated with users based in part on content of the structured message (see at least paragraph 24 identifies PSAP CPE); and
providing alerts of the event to the user devices based in part on the structured message and user preferences of the users (see at least paragraph 25 sends output message).
Ginter et al specifically does not disclose prompting a large language model to generate a structured message from the CAD message in the first format;
prompting the large language model to generate announcement text, wherein the announcement text is based in part on the CAD message.
However, Dan et al from the same or similar fields of endeavor teaches prompting a large language model to generate a structured message from the CAD message in the first format (see at least paragraph 69);
prompting the large language model to generate announcement text, wherein the announcement text is based in part on the CAD message (see at least paragraph 69).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention was made to modify to incorporate above mention feature as taught by Dan et al into the system of Ginter et al for purpose of providing a prompt to a large language models that include multiple messages.
Regarding claim 2, Ginter et al discloses extracting a street address from the structured message; converting the street address to geographic coordinates; and updating the structured message with geographic coordinates (see at least paragraph 18).
Regarding claim 4, Dan et al discloses prompting the large language model to generate the structured message from the CAD message in the first format, further comprises: prompting the large language model to generate a title for the structured message using the CAD message (see at least paragraph 69). Same motivation as claim 1.
Regarding claim 6, Ginter et al discloses converting the announcement text to audio data that corresponds to the announcement text, wherein providing the alerts of the event to the user devices associated with users based in part on the structured message and user preferences for the users, further comprises: determining a user preference for a user of a user device of the user devices, to have alerts sent to the user device via a wireless broadcast, wherein the audio data is provided to the user device via a wireless broadcast (see at least paragraph 25).
Regarding claim 7, Dan et al discloses prompting the large language model to generate the announcement text, comprises: prompting the large language model to generate the announcement text using the structured message (see at least paragraph 69). Same motivation as claim 1.
Regarding claim 8, Dan et al discloses prompting the large language model to generate the announcement text, comprises: prompting the large language model to generate announcement text using the CAD message (see at least paragraph 69). Same motivation as claim 1.
Regarding claim 9, Dan et al discloses prompting the large language model to generate announcement text using the CAD message is performed in parallel with prompting the large language model to generate the structured message from the CAD message in the first format (see at least paragraph 69). Same motivation as claim 1.
Regarding claim 10, Ginter et al discloses providing a user interface to a user device, of the user devices, the user interface presenting one or more alerts that have been provided to the user device; receiving, from the user device, a selection of an alert of the one or more alerts; retrieving an event record based in part on the selection; and presenting based in part on the event record, information from the alert, a CAD message associated with the alert, and an option to provide feedback regarding the alert (see at least paragraph 25).
Regarding claim 11, Dan et al discloses generating a prompt using the CAD message, instructions to generate the structured message from the CAD message, and contextual information, wherein the contextual information includes at least one specific training example approved by a user associated with a user device of the user devices (see at least paragraph 69). Same motivation as claim 1.
Regarding claim 12, Ginter et al discloses the dispatch service provides the CAD message to a set of user devices that are associated with users, and providing the alerts of the event to the user devices based in part on the structured message and user preferences of the users comprises: providing an alert to a user device that is associated with a user who is not one of the users associated with the set of user devices (see at least paragraph 25).
Regarding claim 13, Ginter et al discloses a computer program product comprising a non-transitory computer readable storage medium having instructions encoded thereon that, when executed by a processor of a computer system, cause the computer system to perform steps comprising:
receiving, from a dispatch service of a plurality of dispatch services, a computer aided dispatch (CAD) message describing an event and the CAD message is in a first format, where at least some of the plurality of dispatch services generate CAD messages that are in a format other than the first format (see at least paragraphs 15 and 21 receiving emergency event message);
identifying user devices that are associated with users based in part on content of the structured message (see at least paragraph 24 identifies PSAP CPE); and
providing alerts of the event to the user devices based in part on the structured message and user preferences of the users (see at least paragraph 25 sends output message).
Ginter et al specifically does not disclose prompting a large language model to generate a structured message from the CAD message in the first format.
However, Dan et al from the same or similar fields of endeavor teaches prompting a large language model to generate a structured message from the CAD message in the first format (see at least paragraph 69).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention was made to modify to incorporate above mention feature as taught by Dan et al into the system of Ginter et al for purpose of providing a prompt to a large language models that include multiple messages.
Regarding claim 14, Ginter et al discloses extracting a street address from the structured message; converting the street address to geographic coordinates; and updating the structured message with geographic coordinates (see at least paragraph 18).
Regarding claim 16, Dan et al discloses the encoded instructions for prompting the large language model to generate the structured message from the CAD message in the first format cause the computer system to perform steps comprising: prompting the large language model to generate a title for the structured message using the CAD message (see at least paragraph 69). Same motivation as claim 1.
Regarding claim 17, Ginter et al discloses prompting the large language model to generate announcement text, wherein the announcement text is based in part on the CAD message; and converting the announcement text to audio data that corresponds to the announcement text, wherein the encoded instructions for providing the alerts of the event to the user devices associated with users based in part on the structured message and user preferences for the users cause the computer system to perform steps comprising: determining a user preference for a user of a user device of the user devices, to have alerts sent to the user device via a wireless broadcast, wherein the audio data is provided to the user device via a wireless broadcast (see at least paragraph 25).
Regarding claim 18, Dan et al discloses the encoded instructions for prompting the large language model to generate the announcement text cause the computer system to perform steps comprising: prompting the large language model to generate the announcement text using the structured message (see at least paragraph 69). Same motivation as claim 1.
Regarding claim 19, Ginter et al discloses the dispatch service provides the CAD message to a set of user devices that are associated with users, and the encoded instructions for providing the alerts of the event to the user devices based in part on the structured message and user preferences of the users cause the computer system to perform steps comprising: providing an alert to a user device that is associated with a user who is not one of the users associated with the set of user devices (see at least paragraph 25).
Regarding claim 20, Ginter et al discloses a computer system comprising: a processor; and a non-transitory computer readable storage medium having instructions encoded thereon that, when executed by the processor, cause the computer system to perform steps comprising:
receiving, from a dispatch service of a plurality of dispatch services, a computer aided dispatch (CAD) message describing an event and the CAD message is in a first format, where at least some of the plurality of dispatch services generate CAD messages that are in a format other than the first format (see at least paragraphs 15 and 21 receiving emergency event message),
identifying user devices that are associated with users based in part on content of the structured message (see at least paragraph 24 identifies PSAP CPE), and
providing alerts of the event to the user devices based in part on the structured message and user preferences of the users (see at least paragraph 25 sends output message).
Ginter et al specifically does not disclose prompting a large language model to generate a structured message from the CAD message in the first format.
However, Dan et al from the same or similar fields of endeavor teaches prompting a large language model to generate a structured message from the CAD message in the first format (see at least paragraph 69).
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention was made to modify to incorporate above mention feature as taught by Dan et al into the system of Ginter et al for purpose of providing a prompt to a large language models that include multiple messages.
Allowable Subject Matter
Claims 3, 5 and 15 objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
The prior art made of record and not relied upon is considered pertinent to Applicant's disclosure.
The following prior art are cited to show a method, which is considered pertinent to the claimed invention:
Sampath (US Pat. Pub. No. 2024/0354176) directed toward notification messages generated by a generative language model.
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/LITON MIAH/ Primary Examiner, Art Unit 2642
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