DETAILED ACTION
Remarks
This office action is issued in response to communication filed on 5/9/2023. Claims 1-6,8,11-12,14-16,18,20-25 and 27 are pending in this Office 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 Objections
Claims 1 and 21 are objected to because of the following informalities: Claims 1 and 21 recite the term "parent/child". It is not clear what the symbol “/” refers to . Appropriate correction is required.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the claims at issue are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); and In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on a nonstatutory double patenting ground provided the reference application or patent either is shown to be commonly owned with this application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The USPTO internet Web site contains terminal disclaimer forms which may be used. Please visit http://www.uspto.gov/forms/. The filing date of the application will determine what form should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to http://www.uspto.gov/patents/process/file/efs/guidance/eTD-info-I.jsp.
Claims 1-6,8,11-12 ,14-16,18,20-25 and 27 are rejected on the ground of nonstatutory obviousness type double patenting as being unpatentable over claims 1-6,8,11-12 ,14-16,18,20-25 and 27 respectively of US Patent 11,314,922 B2 hereinafter “922 patent”. Although the claims at issue are not identical, they are not patentably distinct from each other because all the elements of the instant application claims 1-6,8,11-12 ,14-16,18,20-25 and 27 are to be found in the claims1-6,8,11-12 ,14-16,18,20-25 and 27 respectively of the 922 patent.
Instant Application (18/252,282)
US Patent 11,314,922 B2
1. (Currently amended) A computer-implemented method for generating regulatory content requirement descriptions, the method comprising: receiving a plurality of requirements extracted from regulatory content, wherein each requirement within the plurality of requirements is associated with a hierarchical level;
identifying parent requirements within the plurality of requirements based on the existence of one or more child requirements on a hierarchical level immediately below the parent requirement;
generating requirement pairs, each requirement pair including a parent requirement of the parent requirements and at least one child requirement of the one or more child requirements on the hierarchical level immediately below the parent requirement;
feeding a requirement pair of the requirement pairs through a conjunction classifier, the conjunction classifier trained to generate a classification output indicative of the requirement pair being one of:
a single requirement conjunction (CSR) between the parent requirement and the at least one child requirement; or
a multiple requirement conjunction (CMR) between the parent requirement and the at least one child requirement; and
generating requirement description based on the classification output generated for the parent requirement.
1. A computer-implemented method for generating regulatory content requirement descriptions, the method comprising: receiving requirement data including a plurality of requirements extracted from regulatory content, the requirement data including hierarchical information identifying a hierarchical level of each requirement within the plurality of requirements;
identifying parent requirements within the plurality of requirements based on the existence of one or more child requirements on a hierarchical level immediately below the parent requirement;
generating requirement pairs, each pair including one of the parent requirements and at least one of the one or more child requirements on the hierarchical level immediately below the parent requirement;
feeding each of the requirement pairs through a conjunction classifier, the conjunction classifier having been trained to generate a classification output indicative of the requirement pair being one of:
not a conjunction (NC) between the parent requirement and the child requirement;
a single requirement conjunction (CSR) between the parent requirement and the child requirement; or a multiple requirement conjunction (CMR) between the parent requirement and the child requirement; and generating a set of requirement descriptions based on the classification output generated for each parent requirement.
2. (Currently amended) The method of claim 1 wherein generating the requirement pairs comprises generating a single requirement pair for the parent requirement, the single requirement pair including the parent requirement and all of the one or more child requirements on the hierarchical level immediately below the parent requirement.
3. (Currently amended) The method of claim 1 wherein generating the requirement pairs comprises generating a plurality of separate requirement pairs for the parent requirement, each separate requirement pair of the plurality of separate requirement pairs including the parent requirement and one of the one or more child requirements on the hierarchical level immediately below the parent requirement.
4. (Currently amended) The method of claim 3 further comprising generating a final classification for the parent requirement based on a combination of classification outputs for the plurality of separate requirement pairs.
5. (Currently amended) The method of claim 4 wherein generating the final classification for the parent requirement comprises one or more of:
feeding the classification outputs for the plurality of separate requirement pairs through a final classification neural network, the final classification neural network trained to generate the final classification based on the combination of the classification outputs for the plurality of separate requirement pairs;
performing majority voting using the classification outputs for the plurality of separate requirement pairs; and
prioritizing a classification output of CSR by assigning the classification output of CSR to the parent requirement when any one of the classification outputs associated with the plurality of separate requirement pairs is assigned CSR.
6. (Currently amended) The method of claim 14 wherein the conjunction classifier is further trained to generate a classification output indicative of the requirement pair being not a conjunction (NC) between the parent requirement and the at least one child requirement.
8. The method of claim 6 wherein generating the requirement descriptions comprises:
in response to the parent requirement being assigned a classification output of NC , generating a requirement description that includes text associated only with the parent requirement;
in response to the parent requirement being assigned a classification output of CSR , generating a single requirement description that concatenates text associated with the parent requirement and each of the one or more child requirements at the hierarchical level below the parent requirement; and
in response to the for each parent requirement being assigned a classification output of CMR classification, generating a separate requirement description that concatenates text associated with the parent requirement and the text of each of the one or more child requirements at the hierarchical level below the parent requirement.
11. (Currently amended) The method of claim 8 further comprising assigning
a requirement label (REQ) for:
each parent requirement of the parent requirements that is assigned a final classification of CSR;
and
each child requirement of the one or more child requirements associated with a parent requirement assigned a final classification of CMR; and
a requirement addressed elsewhere (RAE) label for each parent requirement of the parent requirements assigned a final classification of CMR.
12. (Currently amended) The method of claim 1 wherein receiving the plurality of requirements comprises:
receiving the regulatory content and generating a language embedding output representing the regulatory content, wherein the language embedding output is generated using a pre-trained language model fine-tuned using a corpus of unlabeled regulatory content; processing the language embedding output to identify citations and associated requirements within the regulatory content; and
processing citations to determine a hierarchical level for each of the citations and associated requirement.
14. (Currently amended) The method of claim 1 further comprising :
configuring the a conjunction classifier neural network to generate the classification output, the conjunction classifier comprising a conjunction classifier neural network having a plurality of weights and biases set to an initial value;
in a training exercise, feeding a training set of requirement pairs through the conjunction classifier, each requirement pair in the training set having a label indicating whether the requirement pair is a CSR requirement pair or a CMR requirement pair; and
based on the classification output by the conjunction classifier for requirement pairs in the training set, optimizing the plurality of weights and biases to train the conjunction classifier neural network for generation of the classification output.
15. (Currently amended) The method of claim 1 further comprising generating a requirement summarizations corresponding to the requirement descriptions and summarizing a text content of the requirement description.
16. (Currently amended) The method of claim 15 wherein generating the requirement summarizations comprises feeding each of the requirement descriptions through a summarization generator, the summarization generator being implemented using a summarization generator neural network trained to generate a summarization output based on a text input.
18. (Currently amended) The method of claim 16 further comprising training the summarization generator neural network by:
identifying requirements in regulatory content;
generating training data in which the identified requirements are masked while leaving descriptive text, optional requirements, and recommendations unmasked; training the summarization generator neural network using the training data; and
fine-tuning the summarization generator neural network using a regulatory content dataset including requirement descriptions and corresponding requirement description summaries.
20. (Currently amended) The method of claim 16 further comprising training the summarization generator neural network by:
extracting requirements from a plurality of different regulatory content sources to generate a requirement corpus;
generating language embeddings for the requirement sentences in the requirement corpus; identifying similar requirement sentences within the requirement corpus that meet a similarity threshold based on their respective language embeddings; and
for each of the similar requirement sentences, generating a control token that is based on attributes of the requirement sentence to generate labeled training samples for training the summarization generator neural network.
21. (Currently amended) A system for generating regulatory content requirement descriptions, the system comprising:
a parent/child relationship identifier, configured to:
receive a plurality of requirements extracted from regulatory content, wherein each requirement within the plurality of requirements is associated with a hierarchical level;
identify parent requirements within the plurality of requirements based on existence of one or more child requirements on a hierarchical level immediately below the parent requirement; and
generate requirement pairs, each requirement pair including a parent requirement of the parent requirements and at least one child requirement of the one or more child requirements on the hierarchical level immediately below the parent requirement;
a conjunction classifier configured to receive a requirement pair of the requirement pairs, the conjunction classifier trained to generate a classification output indicative of the requirement pair being one of:
a single requirement conjunction (CSR) between the parent requirement and the at least one child requirement; or a multiple requirement conjunction (CMR) between the parent requirement and the at least one child requirement;
a requirement description generator configured to generate a requirement descriptions based on the classification output generated for each the parent requirement.
22. (Currently amended) The system of claim 21 wherein the parent/child relationship identifier is configured to generate the requirement pairs by generating a single requirement pair for the parent requirement, the single requirement pair including the parent requirement and all of the one or more child requirements on the hierarchical level immediately below the parent requirement.
23. (Currently amended) The system of claim 21 wherein the parent/child relationship identifier is configured to generate the requirement pairs by generating a plurality of separate requirement pairs for each the parent requirement, each separate requirement pair of the plurality of separate requirement pairs including the parent requirement and one of the one or more child requirements on the hierarchical level immediately below the parent requirement.
24. (Currently amended) The system of claim 23 wherein the requirement description generator is configured to generate a final classification for the parent requirement based on a combination of the classification outputs for the plurality of separate requirement pairs by one or more of:
feeding the classification outputs for the plurality of separate requirement pairs through a final classification neural network, the final classification neural network trained to generate the final classification based on the combination of the classification outputs for the plurality of separate requirement pairs; performing majority voting using the classification outputs for the plurality of separate requirement pairs; and prioritizing a classification output of CSR by assigning the classification output of CSR to the parent requirement when any one of the classification outputs associated with the plurality of separate requirement pairs is assigned CSR.
25. (Currently amended) The system of claim 21 wherein the conjunction classifier is further trained to generate a classification output indicative of the requirement pair being not a conjunction (NC) between the parent requirement and the at least one child requirement.
27. (Currently amended) The system of claim 21 further comprising a summarization generator operably configured to generate a requirement summarizations, corresponding to the requirement descriptions and summarizing a text content of the requirement description.
2. The method of claim 1 wherein generating the requirement pairs comprises generating a single requirement pair for each parent requirement, the single requirement pair including the parent requirement and all of the child requirements on the hierarchical level immediately below the parent requirement.
3. The method of claim 1 wherein generating the requirement pairs comprises generating a plurality of separate requirement pairs for each parent requirement, each separate requirement pair including the parent requirement and one of the one or more child requirements on the hierarchical level immediately below the parent requirement.
4. The method of claim 3 further comprising generating a final classification for each parent requirement based on a combination of the classification outputs for the requirement pairs corresponding to the one or more child requirements on a hierarchical level immediately below the parent requirement.
5. The method of claim 4 wherein generating the final classification for each parent requirement comprises
feeding the classification output for each parent requirement through a final classification neural network, the final classification neural network having been trained to generate the final classification based on the combination of the classification outputs for the requirement pairs.
6. The method of claim 4 wherein generating the final classification comprises assigning a final classification to a parent requirement based on the classifications assigned by the conjunction classifier to the requirement pairs associated with the parent requirement on a majority voting basis.
8. The method of claim 1 wherein generating the set of requirement descriptions comprises:
for each parent requirement assigned a NC classification, generating a requirement description that includes text associated only with the parent requirement;
for each parent requirement assigned a CSR classification, generating a single requirement description that concatenates text associated with the parent requirement and each of the one or more child requirements at the hierarchical level below the parent requirement; and
for each parent requirement assigned a CMR classification, generating a separate requirement description that concatenates text associated with the parent requirement and the text of each of the one or more child requirements at the hierarchical level below the parent requirement.
11. The method of claim 10 wherein generating the spreadsheet listing further comprises, generating a label column, the label column including: a requirement label (REQ) for each of: a parent requirement that is assigned a final classification of CSR
a child requirement associated with a parent requirement assigned a final classification of CMR; and
a requirement addressed elsewhere (RAE) label for each parent requirement assigned a final classification of CMR.
12. The method of claim 1 wherein receiving the plurality of requirements comprises:
receiving regulatory content and generating a language embedding output representing the regulatory content; processing the language embedding output to identify citations and associated requirements within the regulatory content; and processing the plurality of citations to determine a hierarchical level for the citation and associated requirement.
14. The method of claim 1 further comprising, prior to generating regulatory content requirement descriptions: configuring a conjunction classifier neural network to generate the classification output, the conjunction classifier neural network having a plurality of weights and biases set to an initial value;
in a training exercise, feeding a training set of requirement pairs through the conjunction classifier, each requirement pair in the training set having a label indicating whether the pair is a NC, CSR, or CMR requirement pair; and
based on the classification output by the conjunction classifier neural network for requirement pairs in the training set, optimizing the plurality of weights and biases to train the neural network for generation of the classification output.
15. The method of claim 1 further comprising generating a plurality of requirement summarizations, each requirement summarization corresponding to one of the requirement descriptions and summarizing a text content of the requirement description.
16. The method of claim 15 wherein generating the plurality of requirement summarizations comprises feeding each of the requirement descriptions through a summarization generator, the summarization generator being implemented using a summarization generator neural network that has been trained to generate a summarization output based on a text input.
18. The method of claim 17 further comprising training the summarization generator neural network by:
identifying requirements in regulatory content;
generating training data in which the identified requirements are masked while leaving descriptive text, optional requirements, and recommendations unmasked; training the summarization generator neural network using the training data;
fine-tuning the summarization generator neural network using a regulatory content dataset including requirement descriptions and corresponding requirement description summaries.
20. The method of claim 17 further comprising training the summarization generator neural network by:
extracting requirements from a plurality of different regulatory content sources to generate a requirement corpus;
generating language embeddings for the requirement sentences in the requirement corpus; identifying similar requirement sentences within the requirement corpus that meet a similarity threshold based on their respective language embeddings;
for each of the identified similar requirement sentences, generating a control token that is based on attributes of the requirement sentence to generate labeled training samples for training summarization generator neural network.
21. A system for generating regulatory content requirement descriptions, the system comprising:
a parent/child relationship identifier, configured to:
receive requirement data including a plurality of requirements extracted from regulatory content, the requirement data including hierarchical information identifying a hierarchical level of each requirement within the plurality of requirements;
identify parent requirements within the plurality of requirements based on the existence of one or more child requirements on a hierarchical level immediately below the parent requirement;
generate requirement pairs, each pair including one of the parent requirements and at least one of the one or more child requirements on the hierarchical level immediately below the parent requirement;
a conjunction classifier configured to receive each of the requirement pairs, the conjunction classifier having been trained to generate a classification output indicative of the requirement pair being one of:
not a conjunction (NC) between the parent requirement and the child requirement;
a single requirement conjunction (CSR) between the parent requirement and the child requirement; or a multiple requirement conjunction (CMR) between the parent requirement and the child requirement; a requirement description generator configured to generate a set of requirement descriptions based on the classification output generated for each parent requirement.
22. The system of claim 21 wherein the parent/child relationship identifier is configured to generate the requirement pairs by generating a single requirement pair for each parent requirement, the single requirement pair including the parent requirement and all of the child requirements on the hierarchical level immediately below the parent requirement.
23. The system of claim 21 wherein the parent/child relationship identifier is configured to generate the requirement pairs by generating a plurality of separate requirement pairs for each parent requirement, each separate requirement pair including the parent requirement and one of the one or more child requirements on the hierarchical level immediately below the parent requirement.
24. The system of claim 23 wherein the requirement description generator is configured to generate a final classification for each parent requirement based on a combination of the classification outputs for the requirement pairs corresponding to the one or more child requirements on a hierarchical level immediately below the parent requirement.
See claim 21 above that recites the limitation of “a conjunction classifier configured to receive each of the requirement pairs, the conjunction classifier having been trained to generate a classification output indicative of the requirement pair being one of: not a conjunction (NC) between the parent requirement and the child requirement”
27. The system of claim 21 further comprising a summarization generator operably configured to generate a plurality of requirement summarizations, each requirement summarization corresponding to one of the requirement descriptions and summarizing a text content of the requirement description.
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 1-6,8,11-12,14-16,18,20-25 and 27 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claims 1 and 21:
Step 1: Statutory Category ?: Yes. claim 1 recites a method (i.e., a “process”) and claim 21 recites a system (i.e., a “machine”) , and which are statutory categories.
Claim 1:
Step 2A-Prong 1: Judicial Exception Recited ?: Yes.
The limitation “identifying parent requirements within the plurality of requirements based on the existence of one or more child requirements on a hierarchical level immediately below the parent requirement” is a mental process that can be performed in the human mind using observation, evaluation, judgment and opinion including with the help of a pen and paper.
Step 2A-Prong 2: Integrated into a practical application? No.
Claim 1 recites additional elements of:
receiving a plurality of requirements extracted from regulatory content, wherein each requirement within the plurality of requirements is associated with a hierarchical level;
generating requirement pairs, each requirement pair including a parent requirement of the parent requirements and at least one child requirement of the one or more child requirements on the hierarchical level immediately below the parent requirement;
generating requirement description based on the classification output generated for the parent requirement.
These additional elements are pre/post solution activity which is insignificant extra-solution activities. (See MPEP 2106.05(g)).
The additional element of : “feeding a requirement pair of the requirement pairs through a conjunction classifier, the conjunction classifier trained to generate a classification output indicative of the requirement pair being one of:
a single requirement conjunction (CSR) between the parent requirement and the at least one child requirement; or a multiple requirement conjunction (CMR) between the parent requirement and the at least one child requirement” amounts no more than using generic computer with generic classifier to apply the abstract idea (See MPEP 2106.05(f)).
Step 2B: Recites additional elements that amount to significantly more than the judicial exception? No.
Claim 1 does not include additional elements that are sufficient to amount to significantly more than judicial exception. As indicates above, the additional element of using classifier to generate classification output is at best the equivalent of merely adding the words “apply it” to the exception. The additional elements of receiving and generating are data gathering and are well-understood, routine conventional activities previously known to the industry and therefore do not amount to significantly more than the judicial exception. (See MPEP 2106.05(d)) , Subsection II. Even when considered in combination, the additional elements do not provide an inventive concept, claim 1 therefore is ineligible.
Claim 2 recites the additional limitation of : “wherein generating the requirement pairs comprises generating a single requirement pair for the parent requirement, the single requirement pair including the parent requirement and all of the one or more child requirements on the hierarchical level immediately below the parent requirement” which is pre/post solution activity which is insignificant extra-solution activities. (See MPEP 2106.05(g)). Claim 2 does not include any additional element that integrates the abstract idea into practical application in step 2A-Prong 2 and amounts to significantly more than the judicial exception in step 2B. Claim 2 is not patent eligible.
Claim 3 recites the additional limitation of: “wherein generating the requirement pairs comprises generating a plurality of separate requirement pairs for the parent requirement, each separate requirement pair of the plurality of separate requirement pairs including the parent requirement and one of the one or more child requirements on the hierarchical level immediately below the parent requirement” which is pre/post solution activity which is insignificant extra-solution activities. (See MPEP 2106.05(g)). Claim 3 does not include any additional element that integrates the abstract idea into practical application in step 2A-Prong 2 and amounts to significantly more than the judicial exception in step 2B. Claim 3 is not patent eligible.
Claim 4 recites the additional limitation of “generating a final classification for the parent requirement based on a combination of classification outputs for the plurality of separate requirement pairs” amounts no more than using generic computer with generic classification model to apply the abstract idea and at best the equivalent of merely adding the words “apply it” to the exception. Even when considered in combination, the additional elements do not provide an inventive concept, claim 4 therefore is ineligible.
Claim 5 recites the additional limitation of “wherein generating the final classification for the parent requirement comprises one or more of:
feeding the classification outputs for the plurality of separate requirement pairs through a final classification neural network, the final classification neural network trained to generate the final classification based on the combination of the classification outputs for the plurality of separate requirement pairs;
performing majority voting using the classification outputs for the plurality of separate requirement pairs; and
prioritizing a classification output of CSR by assigning the classification output of CSR to the parent requirement when any one of the classification outputs associated with the plurality of separate requirement pairs is assigned CSR” which amounts no more than using generic computer with generic classification model to apply the abstract idea and at best the equivalent of merely adding the words “apply it” to the exception. Even when considered in combination, the additional elements do not provide an inventive concept, claim 5 therefore is ineligible.
Claim 6 recites the additional limitation of “wherein the conjunction classifier is further trained to generate a classification output indicative of the requirement pair being not a conjunction (NC) between the parent requirement and the at least one child requirement” which amounts to no more than mere instructions to implement an abstract idea on a generic computer and is equivalent of adding the words “apply it” to the judicial exception. Even when considered in combination, the additional elements do not provide an inventive concept, claim 6 therefore is ineligible.
Claim 8 recites the additional limitations of “wherein generating the requirement descriptions comprises: in response to the parent requirement being assigned a classification output of NC , generating a requirement description that includes text associated only with the parent requirement; in response to the parent requirement being assigned a classification output of CSR , generating a single requirement description that concatenates text associated with the parent requirement and each of the one or more child requirements at the hierarchical level below the parent requirement; and in response to the for each parent requirement being assigned a classification output of CMR classification, generating a separate requirement description that concatenates text associated with the parent requirement and the text of each of the one or more child requirements at the hierarchical level below the parent requirement” which amounts to no more than mere instructions to implement an abstract idea on a generic computer and is equivalent of adding the words “apply it” to the judicial exception. Even when considered in combination, the additional elements do not provide an inventive concept, claim 8 therefore is ineligible.
Claim 11 recites the additional limitations of “ assigning a requirement label (REQ) for: each a-parent requirement of the parent requirements that is assigned a final classification of CSR; and each child requirement of the one or more child requirements associated with a parent requirement assigned a final classification of CMR; and a requirement addressed elsewhere (RAE) label for each parent requirement of the parent requirements assigned a final classification of CMR” which is a mental process that can be performed in the human mind using observation, evaluation, judgment and opinion including with the help of a pen and paper. Claim 11 does not include any additional element that integrates the abstract idea into practical application in step 2A-Prong 2 and amounts to significantly more than the judicial exception in step 2B. Claim 11 is not patent eligible.
Claim 12 recites the additional limitations of “wherein receiving the plurality of requirements comprises: receiving the regulatory content and generating a language embedding output representing the regulatory content, wherein the language embedding output is generated using a pre-trained language model fine-tuned using a corpus of unlabeled regulatory content; processing the language embedding output to identify citations and associated requirements within the regulatory content; and processing citations to determine a hierarchical level for each of the citations and associated requirement” which is mere data gathering and is insignificant extra-solution activities. (See MPEP 2106.05(g)) and does not amount to significantly more than the judicial exception. Even when considered in combination, the additional elements do not provide an inventive concept, claim 12 therefore is ineligible.
Claim 14 recites the additional limitations of “configuring the a conjunction classifier neural network to generate the classification output, the conjunction classifier comprising a conjunction classifier neural network having a plurality of weights and biases set to an initial value; in a training exercise, feeding a training set of requirement pairs through the conjunction classifier, each requirement pair in the training set having a label indicating whether the requirement pair is a CSR requirement pair or a CMR requirement pair; and based on the classification output by the conjunction classifier for requirement pairs in the training set, optimizing the plurality of weights and biases to train the conjunction classifier neural network for generation of the classification output” which amounts to no more than mere instructions to implement an abstract idea on a generic computer and is equivalent of adding the words “apply it” to the judicial exception. Even when considered in combination, the additional elements do not provide an inventive concept, claim 14 therefore is ineligible.
Claim 15 recites the additional limitation of “generating a requirement summarizations corresponding to the requirement descriptions and summarizing a text content of the requirement description” which amounts to no more than mere instructions to implement an abstract idea on a generic computer and is equivalent of adding the words “apply it” to the judicial exception. Even when considered in combination, the additional elements do not provide an inventive concept, claim 15 therefore is ineligible.
Claim 16 recites the additional limitation of “wherein generating the requirement summarizations comprises feeding each of the requirement descriptions through a summarization generator, the summarization generator being implemented using a summarization generator neural network trained to generate a summarization output based on a text input” which amounts to no more than mere instructions to implement an abstract idea on a generic computer and is equivalent of adding the words “apply it” to the judicial exception. Even when considered in combination, the additional elements do not provide an inventive concept, claim 16 therefore is ineligible.
Claim 18 recites the additional limitation of “training the summarization generator neural network by: identifying requirements in regulatory content;
generating training data in which the identified requirements are masked while leaving descriptive text, optional requirements, and recommendations unmasked; training the summarization generator neural network using the training data; and fine-tuning the summarization generator neural network using a regulatory content dataset including requirement descriptions and corresponding requirement description summaries” which amounts to no more than mere instructions to implement an abstract idea on a generic computer and is equivalent of adding the words “apply it” to the judicial exception. Even when considered in combination, the additional elements do not provide an inventive concept, claim 18 therefore is ineligible.
Claim 20 recites the additional limitation of “training the summarization generator neural network by: extracting requirements from a plurality of different regulatory content sources to generate a requirement corpus; generating language embeddings for the requirement sentences in the requirement corpus; identifying similar requirement sentences within the requirement corpus that meet a similarity threshold based on their respective language embeddings; and for each of the similar requirement sentences, generating a control token that is based on attributes of the requirement sentence to generate labeled training samples for training the summarization generator neural network” which amounts to no more than mere instructions to implement an abstract idea on a generic computer and is equivalent of adding the words “apply it” to the judicial exception. Even when considered in combination, the additional elements do not provide an inventive concept, claim 20 therefore is ineligible.
Claim 21:
Step 2A-Prong 1: Judicial Exception Recited ?: Yes.
The limitation “identifying parent requirements within the plurality of requirements based on the existence of one or more child requirements on a hierarchical level immediately below the parent requirement” is a mental process that can be performed in the human mind using observation, evaluation, judgment and opinion including with the help of a pen and paper.
Step 2A-Prong 2: Integrated into a practical application? No.
Claim 21 recites additional elements of:
“receiving a plurality of requirements extracted from regulatory content, wherein each requirement within the plurality of requirements is associated with a hierarchical level” which is mere data gathering which is insignificant extra-solution activities. (See MPEP 2106.05(g)).
The additional elements of “generating requirement pairs, each requirement pair including a parent requirement of the parent requirements and at least one child requirement of the one or more child requirements on the hierarchical level immediately below the parent requirement; generating requirement description based on the classification output generated for the parent requirement” which are insignificant extra-solution activities. (See MPEP 2106.05(g)).
The additional element of : “ a conjunction classifier configured to receive a requirement pairs, the conjunction classifier trained to generate a classification output indicative of the requirement pair being one of:
a single requirement conjunction (CSR) between the parent requirement and the at least one child requirement; or a multiple requirement conjunction (CMR) between the parent requirement and the at least one child requirement” amounts no more than using generic computer with generic classifier to apply the abstract idea (See MPEP 2106.05(f)).
The additional elements of “a system comprising a parent/child relationship identifier; a conjunction classifier; a requirement description generator” are recited at the very high level of generality such that it amounts no more than using generic computer with generic classifier, identifier and generator to apply the abstract idea (See MPEP 2106.05(f)).
Step 2B: Recites additional elements that amount to significantly more than the judicial exception? No.
Claim 21 does not include additional elements that are sufficient to amount to significantly more than judicial exception. As indicates above, the additional element of using identifier, classifier and generator is at best the equivalent of merely adding the words “apply it” to the exception. The additional elements of receiving which is data gathering and is well-understood, routine conventional activities previously known to the industry and therefore do not amount to significantly more than the judicial exception. (See MPEP 2106.05(d)) , Subsection II. Even when considered in combination, the additional elements do not provide an inventive concept, claim 21. therefore is ineligible.
Claim 22 recites the additional limitation of “wherein the parent/child relationship identifier is configured to generate the requirement pairs by generating a single requirement pair for the parent requirement, the single requirement pair including the parent requirement and all of the one or more child requirements on the hierarchical level immediately below the parent requirement” which amounts to no more than mere instructions to implement an abstract idea on a generic computer and is equivalent of adding the words “apply it” to the judicial exception. Even when considered in combination, the additional elements do not provide an inventive concept, claim 22 therefore is ineligible.
Claim 23 recites the additional limitation of “wherein the parent/child relationship identifier is configured to generate the requirement pairs by generating a plurality of separate requirement pairs for each the parent requirement, each separate requirement pair of the plurality of separate requirement pairs including the parent requirement and one of the one or more child requirements on the hierarchical level immediately below the parent requirement” which amounts to no more than mere instructions to implement an abstract idea on a generic computer and is equivalent of adding the words “apply it” to the judicial exception. Even when considered in combination, the additional elements do not provide an inventive concept, claim 23 therefore is ineligible.
Claim 24 recites the additional limitation of “wherein the requirement description generator is configured to generate a final classification for the parent requirement based on a combination of the classification outputs for the plurality of separate requirement pairs by one or more of:
feeding the classification outputs for the plurality of separate requirement pairs through a final classification neural network, the final classification neural network trained to generate the final classification based on the combination of the classification outputs for the plurality of separate requirement pairs; performing majority voting using the classification outputs for the plurality of separate requirement pairs; and prioritizing a classification output of CSR by assigning the classification output of CSR to the parent requirement when any one of the classification outputs associated with the plurality of separate requirement pairs is assigned CSR” which amounts to no more than mere instructions to implement an abstract idea on a generic computer and is equivalent of adding the words “apply it” to the judicial exception. Even when considered in combination, the additional elements do not provide an inventive concept, claim 24 therefore is ineligible.
Claim 25 recites the additional limitation of “wherein the conjunction classifier is further trained to generate a classification output indicative of the requirement pair being not a conjunction (NC) between the parent requirement and the at least one child requirement” which amounts to no more than mere instructions to implement an abstract idea on a generic computer and is equivalent of adding the words “apply it” to the judicial exception. Even when considered in combination, the additional elements do not provide an inventive concept, claim 25 therefore is ineligible.
Claim 27 recites the additional limitation of “a summarization generator operably configured to generate a requirement summarizations, corresponding to the requirement descriptions and summarizing a text content of the requirement description” which amounts to no more than mere instructions to implement an abstract idea on a generic computer and is equivalent of adding the words “apply it” to the judicial exception. Even when considered in combination, the additional elements do not provide an inventive concept, claim 27 therefore is ineligible.
Claim Interpretation
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: "a parent/child relationship identifier, configured to: receive a plurality of requirements extracted from regulatory content”; “ a conjunction classifier configured to receive a requirement pair of the requirement pairs” and “a requirement description generator configured to generate a requirement descriptions based on the classification output generated for each the parent requirement” in claim 21.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
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 21-25 and 27 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 pre-AIA the applicant regards as the invention.
Claim 21:
Claim limitations "a parent/child relationship identifier, configured to: receive a plurality of requirements extracted from regulatory content”; “ a conjunction classifier configured to receive a requirement pair of the requirement pairs” and “a requirement description generator configured to generate a requirement descriptions based on the classification output generated for each the parent requirement” invoke 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure for performing the entire claimed function and to clearly link the structure to the function. The examiner is unable to find anywhere in the specification a corresponding structure of “parent/child identifier” that performs the function of “receive a plurality of requirements extracted from regulatory content”; a corresponding structure of “a conjunction classifier” that performs the function of “receive a requirement pair of the requirement pairs” and a corresponding structure of “a requirement description generator” that performs the function of “generate a requirement descriptions based on the classification output generated for each the parent requirement” as recited in claim 21.
Applicant may:
(a) Amend the claim so that the claim limitation will no longer be interpreted as a limitation under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph;
(b) Amend the written description of the specification such that it expressly recites what structure, material, or acts perform the entire claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(c) Amend the written description of the specification such that it clearly links the structure, material, or acts disclosed therein to the function recited in the claim, without introducing any new matter (35 U.S.C. 132(a)).
If applicant is of the opinion that the written description of the specification already implicitly or inherently discloses the corresponding structure, material, or acts and clearly links them to the function so that one of ordinary skill in the art would recognize what structure, material, or acts perform the claimed function, applicant should clarify the record by either:
(a) Amending the written description of the specification such that it expressly recites the corresponding structure, material, or acts for performing the claimed function and clearly links or associates the structure, material, or acts to the claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(b) Stating on the record what the corresponding structure, material, or acts, which are implicitly or inherently set forth in the written description of the specification, perform the claimed function. For more information, see 37 CFR 1.75(d) and MPEP §§ 608.01(o) and 2181.
Due at least to their dependency upon Claims 22-25 and 27 are also indefinite.
Claims 21-25 and 27 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention. Claim 21 recites “parent/child identifier” that performs the function of “receive a plurality of requirements extracted from regulatory content”; “a conjunction classifier” that performs the function of “receive a requirement pair of the requirement pairs” and “a requirement description generator” that performs the function of “generate a requirement descriptions based on the classification output generated for each the parent requirement”. However, the written description fails to disclose the corresponding structure for performing the entire claimed function and to clearly link the structure to the function. Due at least to their dependency upon Claim 21, claims 22-25 and 27 also fail to comply with the written description requirement.
Allowable Subject Matter
Claims 1-6,8,11-12,14-16,18,20-25 and 27 allowed.
Reasons for Allowance
The following is an examiner’s statement of reasons for allowance:
The closest prior art of record, Creed et al.(US Patent Application Publication 2021/0312134 A1, hereinafter “Creed”) and Bangalore et al.(US Patent 8,849,648 B1, hereinafter “Bangalore”) fail to disclose or suggest one or more of the features of the independent claims .
In summary, Creed is directed to an efficient embedding technique for generating a composite embedding from a portion of text including data representative of a relationship with one or more entities of interest (Creed par [0055]) . Creed par [0050] teaches for a corpus of text or plurality of portion of text, there may be a plurality of entity types of interest in which each entity type has a corresponding set of entities that may be identified and/or extracted . Creed par [0057] teaches a hierarchical tree or graph may be used for representing a plurality of entities associated with one or more other entities. Each node of the hierarchical tree represents an entity and each child node of a parent node represents an entity associated with the entity of the parent node. Bangalore is directed to generative and discriminative models for the task of detecting sentence boundaries , identifying speech repairs and editing them out and identifying coordinating conjunctions to break the sentences into clausal units. (Bangalore col 1, lines 65-col 2, line 5) . Bangalore col 2, lines 12-15 teaches a conjunction classifier that detects conjunctions within the text.
None of the prior art of record alone or in any reasonable combination, discloses the claimed invention as recites in the independent claims 1 and 21.Specifically, the prior art fail to teach:
“feeding a requirement pair of the requirement pairs through a conjunction classifier, the conjunction classifier trained to generate a classification output indicative of the requirement pair being one of:
a single requirement conjunction (CSR) between the parent requirement and the at least one child requirement; or
a multiple requirement conjunction (CMR) between the parent requirement and the at least one child requirement; and
generating requirement description based on the classification output generated for the parent requirement” as recited in claim 1 and
“a conjunction classifier configured to receive a requirement pair of the requirement pairs, the conjunction classifier trained to generate a classification output indicative of the requirement pair being one of:
a single requirement conjunction (CSR) between the parent requirement and the at least one child requirement; or a multiple requirement conjunction (CMR) between the parent requirement and the at least one child requirement;
a requirement description generator configured to generate a requirement descriptions based on the classification output generated for each the parent requirement” as recited in claim 21
The recited limitations, in conjunction with all the features of the independent and dependent claims are not taught nor suggested by the prior art of record.
Claims 2-6,8,11-12,14-16,18,20,22-25 and 27 are also allowed as being directly or indirectly dependent of the allowed independent claim.
Conclusion
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/HIEN L DUONG/Primary Examiner, Art Unit 2147