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 § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Regarding claim 1:
Claim one recites “inputting the prompt into an encoder of a pretrained language model;” on line 7 of the claim. However, it is unclear if the recited “a pretrained language model;” is the same or different and distinct “pretrained model” as the previously recited “a pretrained model from lines 1-2 of the claim. Therefore, claim 1 is rejected as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. For the purposes of this office action, claim recited “a pretrained model” of from line 7 of claim 1 is interpreted as being the same as the “a pretrained model” recited in lines 1-2 of the claim.
Dependent claims 2-7 are rejected for containing the same indefinite subject matter of independent claim 1 upon which claims 2-7 depends.
Claim 8 recites the limitation "obtaining the data set and a type of the data processing task to be performed on the data set;" in lines 5-6 of the claim. There is insufficient antecedent basis for this limitation in the claim. Specifically, there is insufficient antecedent basis for “the data set” and “the data processing task.” Therefore, claim 8 is rejected as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Dependent claims 9-14 are rejected for containing the same indefinite subject matter of independent claim 8 upon which claims 9-14 depends.
Claim 15 recites the limitation " obtaining the data set and a type of the data processing task to be performed on the data set;" in lines 4-5 of the claim. There is insufficient antecedent basis for this limitation in the claim. Specifically, there is insufficient antecedent basis for “the data set” and “the data processing task.” Therefore, claim 8 is rejected as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Dependent claims 16-20 are rejected for containing the same indefinite subject matter of independent claim 15 upon which claims 16-20 depends.
Would Be Allowable Subject Matter
Claim 1-20 would be allowable if rewritten or amended to overcome the rejection(s) under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd paragraph, set forth in this Office action.
The following is a statement of reasons for the indication of would be allowable subject matter:
As per claims 1, 8, and 15, taking claim 8 as exemplary:
Though Ye et al., (US 2025/0054322 A1), part of the prior art made of record, teaches the use of token with embeddings and the use of prompts with templates based on ‘types’ of claims 1, 8, and 15 in paragraphs [0075], [0120] and [0125] through the use of prompt templates that can be combined with user input and to use the prompts with attribute types and tokens or embeddings.
And though Bhardwaj et al, (US 2023/0342552 A1), part of the prior art made of record, teaches the use of language models with prompts, embeddings, encoders, and tokens of claims 1, 8, and 15 in paragraphs [0019]-[0021] through the use of prompt tuning of NLP processing tasks that encodes input-adapted prompt tokens that are quantized to reduce noise and mapped the vectors.
And though Jiang et al., ("PromptBERT: Improving BERT Sentence Embeddings with Prompts", Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, pages 8826–8837, (Year: 2022)), part of the prior art made of record, teaches the use of embeddings with prompts and language models and tasks of claims 1, 8, and 15 in page 8833 through the use of a prompt-based embedding method to improve an original BERT layer of a model.
The primary reason for marking of allowable subject matter of independent claims 1, 8, and 15, in the instant application, is the combination with the inclusion in these claims of the limitations of a method, system, and computer program product comprising:
“obtaining the data set and a type of the data processing task to be performed on the data set; generating a prompt by inputting data from the data set into a template, wherein the template is determined based on the type of the data processing task; inputting the prompt into an encoder of a pretrained language model; obtaining, from the encoder, a set of prompt embeddings and a set of token embeddings; inputting the set of prompt embeddings into a trained neural network; obtaining, from the trained neural network, a prefix vector; inputting a set of extended embeddings that are created by appending the set of token embeddings to the prefix vector into a decoder of the pretrained language model; obtaining, from the decoder, an output; and modifying the data set based on the output.”
The prior art of made of record above neither anticipates nor renders obvious the above-recited combinations. Specifically, though the prior art of made of record does teach use of token with embeddings and the use of prompts with templates based on ‘types’; the use of language models with prompts, embeddings, encoders, and tokens; and the use of embeddings with prompts and language models and tasks; it does not teach the use of templates with prompts based on a data processing task in combination with using a prompt with an encoder to obtain token embedding and then inputting that into an already trained neural network, and then subsequently receiving from the trained neural network a prefix vector to create an extended embeddings that is created by appending the set of token embeddings to the prefix vector into a decoder of a trained neural network.
Dependent claim(s) 2-7, 9-14, and 16-20 are marked as would be allowable at least for the reasons recited above as including all of the limitations of the would be allowable independent base claims 1, 8, and 15 upon which claims 2-7, 9-14, and 16-20 depend.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Though Ye et al., (US 2025/0054322 A1), part of the prior art made of record, teaches the use of token with embeddings and the use of prompts with templates based on ‘types’ of claims 1, 8, and 15 in paragraphs [0075], [0120] and [0125] through the use of prompt templates that can be combined with user input and to use the prompts with attribute types and tokens or embeddings.
And though Bhardwaj et al, (US 2023/0342552 A1), part of the prior art made of record, teaches the use of language models with prompts, embeddings, encoders, and tokens of claims 1, 8, and 15 in paragraphs [0019]-[0021] through the use of prompt tuning of NLP processing tasks that encodes input-adapted prompt tokens that are quantized to reduce noise and mapped the vectors.
And though Jiang et al., ("PromptBERT: Improving BERT Sentence Embeddings with Prompts", Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, pages 8826–8837, (Year: 2022)), part of the prior art made of record, teaches the use of embeddings with prompts and language models and tasks of claims 1, 8, and 15 in page 8833 through the use of a prompt-based embedding method to improve an original BERT layer of a model.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SHANE D WOOLWINE whose telephone number is (571)272-4138. The examiner can normally be reached M-F 9:30-6:00 PM.
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SHANE D. WOOLWINE
Primary Examiner
Art Unit 2124
/SHANE D WOOLWINE/Primary Examiner, Art Unit 2124
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