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 .
DETAILED ACTION
Claims 21-40 are pending in this application and have been examined in response to application filed on 10/04/2024.
Claims 1-20 are canceled by the applicant.
CONTINUING DATA: This application is a CON of 18/096,092 01/12/2023 PAT 12229500
Claim Objections
Claim 22 is objected to because of the following informalities: “wherein method…” should have been “wherein the method…”. Appropriate correction is required.
Claim Rejections - 35 USC § 102
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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 21, 26-29, 31 and 36-39 are rejected under 35 U.S.C. 102(a)(1) as being unpatentable by Taslimi et al. (US 2021/0044546 A1).
As to INDEPENDENT claim 21, Taslimi discloses a method executed by an autocomplete prediction engine implemented as a computer program within a computing environment, the autocomplete prediction engine executing automated communication mining, the autocomplete prediction engine being pre-trained to extract intents and entities related to each intent of the intents, the method comprising: extracting and identifying relationships between the intents and the entities related from conversational message data or text of a communication between two or more computers, systems, or users ([0022]-[0024]; intents and entities are mapped from a conversation between a user and a chatbot); and
automatically providing form filling from the conversational message data or text
of the communication using the intents and into the one or more forms ([0025], [0026]; the form is automatically filled based on the gathered information).
As to claim 26, Taslimi discloses, wherein the autocomplete prediction engine achieves conversational or natural language understanding of the communication to ascertain and implement a desire within the communication ([0030], cognitive services are provided a natural language understanding of the conversation).
As to claim 27, Taslimi discloses wherein the communication comprises an email conversation, a service ticket, a short message service message, a transcript, a text message, or a chat message (fig.9; a conversation between a user and a chatbot is conducted).
As to claim 28, Taslimi discloses wherein each intent of the intents comprises a desire, goal, or purpose of the communication or of portions of data in the communication ([0024]; user intent is identified).
As to claim 29, Taslimi discloses wherein each entity of the entities comprises data of the communication ([0022], [0024]; entities are extracted from the conversation).
As to claim 31, it is rejected under the same rationale addressed in the rejection of claim 21 above.
As to claim 36, it is rejected under the same rationale addressed in the rejection of claim 26 above.
As to claim 37, it is rejected under the same rationale addressed in the rejection of claim 27 above.
As to claim 38, it is rejected under the same rationale addressed in the rejection of claim 28 above.
As to claim 39, it is rejected under the same rationale addressed in the rejection of claim 29 above.
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.
Claims 22, 25, 32 and 35 are rejected under 35 U.S.C. 103 as being unpatentable over Taslimi and in view of Muschett et al. (US 2022/0139372 A1).
As to claim 22, Taslimi does not disclose wherein method comprises generating one or
more demarcations for the communication using a language model to provide a conversational or natural language understanding of the communication.
In the same field of endeavor, Muschett discloses generating one or more demarcations for the communication using a language model to provide a conversational or natural language understanding of the communication ([0034]; natural language parsing is utilized).
It would have been obvious to one of ordinary skill in the art, having the teaching of Taslimi and Muschett before him prior to the effective filling date, to modify the form auto completion model taught by Taslimi to include natural language parsing taught by Muschett with the motivation being to allow classifications to be associated with sentence or passage.
As to claim 25, Taslimi does not disclose wherein one or more demarcations respectively corresponding to the intents and the entities.
In the same field of endeavor, Muschett discloses wherein one or more demarcations respectively corresponding to the intents and the entities ([0034]; the input language is parsed to extract intents and entities).
It would have been obvious to one of ordinary skill in the art, having the teaching of Taslimi and Muschett before him prior to the effective filling date, to modify the form auto completion model taught by Taslimi to include natural language parsing taught by Muschett with the motivation being to allow classifications to be associated with sentence or passage.
As to claim 32, it is rejected under the same rationale addressed in the rejection of claim 22 above.
As to claim 35, it is rejected under the same rationale addressed in the rejection of claim 25 above.
Claims 23 and 33 are rejected under 35 U.S.C. 103 as being unpatentable over Taslimi and in view of Shek et al. (US 2021/0165967 A1) and DBpedia (NPL: “DBpedia -A Large-scale, Multilingual Knowledge Base Extracted from Wikipedia).
As to claim 23, Taslimi does not expressly disclose wherein the method comprises generating a pre-training dataset by parsing through each article, a type of each article, abstractions, and structured information in a database to collect at least a plurality of article types.
In the same field of endeavor, Shek discloses generating a pre-training dataset ([0013]; data are extracted from data sources such as DBPedia).
It would have been obvious to one of ordinary skill in the art, having the teaching of Taslimi and Shek before him prior to the effective filling date, to modify the form auto completion model taught by Taslimi to include pre-trained knowledge store from the web taught by Shek with the motivation being to build up a prerequisite knowledge store quickly from existing information extracted from the web. Taslimi-Shek does not expressly disclose parsing through each article, a type of each article, abstractions, and structured information in a database to collect at least a plurality of articles.
In the same field of endeavor, DBpedia discloses parsing through each article, a type of each article, abstractions, and structured information in a database to collect at least a plurality of articles. (pg.3-pg.4; Wikipedia articles are collected and read to extract information such as article categories, abstracts, and infoboxes from the parsed articles).
It would have been obvious to one of ordinary skill in the art, having the teaching of the prior art as combined and DBpedia before him prior to the effective filling date, to modify the form auto completion model taught by the prior art as combined to include a large scale knowledge base taught by DBpedia with the motivation being to reduce overhead by utilize pre-trained data set that is publicly available.
As to claim 33, it is rejected under the same rationale addressed in the rejection of claim 23 above.
Claims 30 and 40 are rejected under 35 U.S.C. 103 as being unpatentable over Taslimi and in view of Chung et al. (NPL, “Scaling Instruction-Finetuned Language Models”).
As to claim 30, Taslimi does not expressly disclose wherein the communication uses language model comprising a FLAN-T5 model.
In the same field of endeavor, Chung discloses a FLAN-T5 model (pg.2, par. “1 Introduction”).
It would have been obvious to one of ordinary skill in the art, having the teaching Taslimi and Chung before him prior to the effective filling date, to modify the form auto completion model taught by Taslimi as combined to include a FLAN-T5 language model taught by Chung with the motivation being to provide improved performance across a range of other language models. (Chung, pg.2).
As to claim 40, it is rejected under the same rationale addressed in the rejection of claim 30 above.
Allowable Subject Matter
Claims 24 and 34 are 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
Any inquiry concerning this communication or earlier communications from the examiner should be directed to HAOSHIAN SHIH whose telephone number is (571)270-1257. The examiner can normally be reached M-F 8:00-5:00.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, FRED EHICHIOYA can be reached at (571) 272-4034. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/HAOSHIAN SHIH/Primary Examiner, Art Unit 2179
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