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
This office action is in response to Applicant’s submission filed on 3/31/2025. Claims 1-20 are pending of which claims 1, and 16 are independent. As such, claims 1-20 have been examined.
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.
Claim 13 is 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.
Claim 13 recites the limitation “the revised text” in lines 1-2. There is insufficient antecedent basis for this limitation in the claim. For the sake of compact prosecution, it will be examine as if the claim depended on claim 12 which recites “a revised text”.
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, and 5-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claim 1 recites a method that, under the broadest reasonable interpretation, claims limitations that cover performance of the limitations in the human mind with the assistance of physical aids (e.g., pen and paper), but for the recitation of generic or well-known or conventional computer components. That is, other than reciting “a neural network”, nothing in these claim limitations precludes the steps from practically being performed in the mind. As a whole, claim 1 pertains to analyzing text, providing comment comparison and determining contradictions between the comments, which a human can do. Individually, each of the limitations also pertains to a mental process and/or methods of organizing human activities, and/or insignificant extra solution activity, for example:
(i) providing a text, as well as a first comment and a second comment associated with the text; (e.g., printing out a paper that has multiple comments or reviews on.)
(ii) defining multiple portions of the text with a neural network; (e.g., highlight or circle portions of the text.)
(iii) associating, by the neural network, each of the first and second comments with one or more corresponding portions of the text to which the comment relates; the one or more corresponding portions of the text being the same or different for the first and second comments; (e.g., analyzing the comments to see which portion of the text they are referencing to by annotating or marking up the paper.)
and (iv) for each portion of the text, determining by the neural network whether the first comment contradicts the second comment, and outputting any contradiction found between the first and second comments. (e.g., analyzing the comments to see if there are contradictions, is comment A opposite of comment B?)
The judicial exception is not integrated into a practical application. In particular, the claims only recites generic computing components. Such generic computing components are recited at a high-level of generality (i.e., as a generic processor performing a generic computer function of receiving, determining, or outputting information) such that they amount to no more than mere instructions to apply the exception using generic computer components. Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
Claim 1 does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional limitations of using generic computer components amount to no more than mere instructions to apply the exception using generic computer components. Mere instructions to apply an exception using generic computer components cannot provide an inventive concept. Claim 1 is not patent eligible.
The examiner further notes that the use of claimed generic computer components (“a neural network”) to obtain, extract, and/or generate data invokes such generic computer components “merely as a tool to perform an existing process”. MPEP 2106.05(f). MPEP 2106.05(f) further explains:
Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). Similarly, "claiming the improved speed or efficiency inherent with applying the abstract idea on a computer" does not integrate a judicial exception into a practical application or provide an inventive concept. Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1367, 115 USPQ2d 1636, 1639 (Fed. Cir. 2015).
Claim 1 recites generic computer components (“a neural network”), with respect to performing tasks. MPEP 2106.05(d) and (f) further provides examples of court decisions where the courts found generic computing components to be mere instructions to apply a judicial exception, and further explains “increased speed” (e.g., using a computer to increase the speed of an otherwise mental process) does not provide an inventive concept. For example:
A commonplace business method or mathematical algorithm being applied on a general purpose computer, Alice Corp. Pty. Ltd. V. CLS Bank Int’l, 573 U.S. 208, 223, 110 USPQ2d 1976, 1983 (2014); Gottschalk v. Benson, 409 U.S. 63, 64, 175 USPQ 673, 674 (1972); Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015).
A process for monitoring audit log data that is executed on a general-purpose computer where the increased speed in the process comes solely from the capabilities of the general-purpose computer, FairWarning IP, LLC v. Iatric Sys., 839 F.3d 1089, 1095, 120 USPQ2d 1293, 1296 (Fed. Cir. 2016) (emphasis added).
Performing repetitive calculations. Bancorp Services v. Sun Life, 687 F.3d 1266, 1278, 103 USPQ2d 1425, 1433 (Fed. Cir. 2012) ("The computer required by some of Bancorp’s claims is employed only for its most basic function, the performance of repetitive calculations, and as such does not impose meaningful limits on the scope of those claims.")
Claim 16 recites system claim that corresponds to the method of claim 1 and is therefore rejected under the same grounds as claim 1 above. While claim 16 further recites “a revision module”, these are merely generic computer components recited at a high-level of generality such that they amount to no more than mere instructions to apply the exception using a generic computer component. Therefore, none of these limitations (a) integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea or (b) amount to significantly more than the judicial exception, because in either case the additional limitations merely utilize generic computer components that amounts to no more than mere instructions to apply the exception using generic computer function. Claim 16 is not patent eligible.
Claims 2-3, 5-15, and 17-20 depend from independent claims 1, and 16, do not remedy any of the deficiencies of claims 1, and 16, and therefore are rejected on the same grounds as claims 1, and 16 from above.
Claim 2 further comprising: further comprising a step of providing an explanation as to why the first and second comments are considered to be in contradiction. (e.g., writing down the reason or rationale on why the comments are on the contrary.)
Claim 3 further comprising: wherein the first comment or the second comment comprises a suggestion for modification of the corresponding portion of the text. (e.g., analyze the comment to determine that one of the comment is a suggestion for modification to a particular portion of the text.)
Claim 5 further recites: wherein the text is generated by the neural network based on an input requirement specified by a user. (e.g., the text could be written by a person upon request of a user, or receiving a text that is generated by ChatGPT.)
Claim 6 further recites: wherein the generation of the text comprising steps of:(i) receiving the input requirement specified by the user;(ii) wrapping the input requirement with a first text template to provide a first input prompt; and(iii) generating, by the neural network, the text based on the first input prompt. (e.g., getting input requirement from a user in a certain format, then a human writer write out a document based on the requirement provided.)
Claim 7 further recites: wherein the input requirement is in a form selected from any one of a text, an image, an audio, and a combination thereof. (e.g., the input requirement can be written in text, shown by the user in a picture, or verbally.)
Claim 8 further recites: wherein the first comment or the second comment is generated by the neural network based on a comment requirement specified by a user. (e.g., a human can make a comment or two based on the comment requirement from a user.)
Claim 9 further recites: wherein the generation of the first comment or the second comment comprises steps of:(i) receiving the comment requirement specified by the user; (ii) wrapping the comment requirement with a second text template to provide a second input prompt; and (iii) generating, by the neural network, the first comment or the second comment based on the second input prompt. (e.g., look at the comment requirement from the user in a text or just listen to what the user has to say, takes notes or fill out a form based on the input requirement, then write up the text or document according to the requirement.)
Claim 10 further recites: wherein the comment requirement is selected from any one of a target number of comments, an objective of comment, and a combination thereof. (e.g., a user can choose the comment requirement, such as number of comments, or an objective for the comments)
Claim 11 further recites: further comprising a step of ignoring at least a part of any one of the first comment and the second comment if the first comment contradicts the second comment, to provide a finalised set of comments comprising one or more comments which do not contradict with each other. (e.g., read the comments and cross out comments that appears to be in disagreement with the others, and write down the list of comments that are in agreement.)
Claim 12 further recites: further comprising a step of modifying the text by the neural network to provide a revised text based on the finalised set of comments. (e.g., edit or rewrite the text based on the finalized set of comments.)
Claim 13 further recites: further comprising a step of checking whether the revised text is amended based on the finalised set of comments, wherein the checking of the revised text comprising steps of:(i) providing the text, the finalised set of comments, and the revised text;(ii) associating, by the neural network, each portion of the text with one or more corresponding portions of the revised text to which the portion of the text most closely resembles;(iii) determining, by the neural network, whether each portion of the revised text is amended based on a corresponding comment within the finalised set of comments. (e.g., check the revision of text, by looking at the original text, the finalized set of comments and the revised text, and label the comments to the relevant portion of text, also determine which or annotate which portion of the revised text is revised based on the finalized comments.)
Claim 14 further recites: further comprising a step of checking whether a revised text is amended based on the first comment or the second comment, wherein the checking of the revised text comprising steps of:(i) providing the text, the first and second comments associated with the text, and the revised text;(ii) associating, by the neural network, each portion of the text with one or more corresponding portions of the revised text to which the portion of the text most closely resembles;(iii) determining, by the neural network, whether each portion of the revised text is amended based on the first comment or the second comment. (e.g., check the revision of text, by looking at the original text, the first and second comments and the revised text, and label the comments to the relevant portion of text, also determine which or annotate which portion of the revised text is revised based on the finalized comments.)
Claim 15 further recites: wherein the neural network is a natural language processing (NLP) model or a large language model (LLM). (e.g., the use of a generic computer component. The human can play the role of the natural language model or LLM.)
Claim 17 is recited similarly to claim 6, therefore the similar rationale and grounds of rejection can be applied.
Claim 18 is recited similarly to claim 14, therefore the similar rationale and grounds of rejection can be applied.
Claim 19 is recited similarly to claim 9, therefore the similar rationale and grounds of rejection can be applied.
Claim 20 is recited similarly to claim 15, therefore the similar rationale and grounds of rejection can be applied.
In sum, claims 2-3, 5-15, and 17-20 depend from claim 1, and 16, and further recite mental processes as explained above. None of the additional limitations recited in claims 2-3, 5-15, and 17-20 amount to anything more than the same or a similar abstract idea as recited in claims 1, and 16. Nor do any limitations in claims 2-3, 5-15, and 17-20: (a) integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea or (b) amount to significantly more than the judicial exception because the additional limitations of using generic computer components amounts to no more than mere instructions to apply the exception using generic computer components. Claims 2-3, 5-15, and 17-20 are not patent eligible.
Patent Claim Eligibility
Claim 4 is not rejected under 101 because obtaining embedding similarity between comments and text is beyond a mental process, and the claim also additionally may have a practical application and provides improvement to the field of AI assisted writing technology.
Claim Rejections - 35 USC § 103
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 1, 3, 5-7, 11-12, 15-17 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Ahmadia (US 20250258874) in view of Chapagain (US 20250371248).
Regarding Claim 1, Ahmadia discloses: 1. A method for associated with the text; ([0093] At block 906, the first generative AI model 125 and/or second generative AI model 126 determines if contradiction exists between the first comment and the second comment. Examples of contradictions include: different classifications of the same document)
(ii) defining multiple portions of the text with a neural network; ([0172] classification model 1102 to identify relevant document portions (e.g., citations, excerpts, etc.) in support of the classification decision. For example, the relevant document portions for a document may be the portions most indicative of responsiveness to an inquiry defined by the prompt criteria 1106.)
(iii) associating, by the neural network, each of the first and second comments with one or more corresponding portions of the text to which the comment relates; ([0093] contradictory indications as to how to classify a type of document (e.g., one comment indicates that spreadsheets are responsive, whereas another comment indicates that spreadsheets are not responsive); contradictions regarding a person (e.g., one comment indicates that emails from the CEO are responsive,) Also see para 0084, 0086, 0094, 0172, 0179-0180 identify the relevant portion of document.
the one or more corresponding portions of the text being the same or different for the first and second comments; ([0093] contradictory indications as to how to classify a type of document (e.g., one comment indicates that spreadsheets are responsive, whereas another comment indicates that spreadsheets are not responsive); contradictions regarding a person (e.g., one comment indicates that emails from the CEO are responsive,) Also see para 0084, 0086, 0094, 0172, 0179-0180 identify the relevant portion of document.
and (iv) for each portion of the text, determining by the neural network whether the first comment contradicts the second comment, ([0093] At block 906, the first generative AI model 125 and/or second generative AI model 126 determines if contradiction exists between the first comment and the second comment.)
and outputting any contradiction found between the first and second comments. ([0133] In response to determining that a contradiction exists, the prompt evaluation application 124 may generate an alert.)
Ahmadia is silent as assisting text writing.
Chapagain in the related art discloses: A method for assisting text writing, ([0053] the initial user input 310-A is a request to generate a patent application, and the prompt engine 236 generates one or more prompts for the large language model 150 using a template for a patent application.
Ahmadia and Chapagain are considered analogous art as they both use llm to process document and receiving user feedback/comment to improve user experience. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Ahmadia to combine the teaching of Chapagain, because LLM can assist user in creating document and improve document updates with user feedback (Chapagain, [0005]).
Regarding Claim 3, Ahmadia and Chapagain disclose all the elements of claim 1,
Chapagain further discloses: wherein the first comment or the second comment comprises a suggestion for modification of the corresponding portion of the text. ([0006] identifying, by the prompt engine, one or more locations within the document that require change based on current content in the document and the user edit; and generating, by the prompt engine, one or more second prompts for the large language model. The one or more second prompts are generated based on the user edit and correspond to the one or more locations within the document. The method also includes receiving second content generated by the large language model based on the one or more second prompts and generating, by the document content manager, an updated document that includes one or more suggestions to update the document with the second content at the one or more locations.)
The rationale for the combination would be similar to the one already provided earlier.
Regarding Claim 5, Ahmadia and Chapagain disclose all the elements of claim 1,
Chapagain further discloses: wherein the text is generated by the neural network based on an input requirement specified by a user. ([0006] receiving an initial input from a user and determining that the initial input corresponds to a request to generate a document having a document type. The method also includes generating, by a prompt engine, one or more first prompts for a large language model.)
The rationale for the combination would be similar to the one already provided earlier.
Regarding Claim 6, Ahmadia and Chapagain disclose all the elements of claim 5,
Chapagain further discloses: wherein the generation of the text comprising steps of:(i) receiving the input requirement specified by the user; ([0006] The one or more first prompts are generated based on (i) the initial input)
(ii) wrapping the input requirement with a first text template to provide a first input prompt; ([0006] (ii) a document template for the document type.)
and(iii) generating, by the neural network, the text based on the first input prompt. ([0006] The method further includes receiving first content generated by the large language model based on the one or more first prompts;)
The rationale for the combination would be similar to the one already provided earlier.
Regarding Claim 7, Ahmadia and Chapagain disclose all the elements of claim 5,
Chapagain further discloses: wherein the input requirement is in a form selected from any one of a text, an image, an audio, and a combination thereof. ([0024] User inputs may be multimodal. For example, user inputs may include, and are not limited to, any combination of text, images, motion, audio, video, sensors.)
The rationale for the combination would be similar to the one already provided earlier.
Regarding Claim 11, Ahmadia and Chapagain disclose all the elements of claim 1,
Ahmadia further discloses: further comprising a step of ignoring at least a part of any one of the first comment and the second comment if the first comment contradicts the second comment, ([0094] If a contradiction is found, the first comment and the second comment are merged based on a priority associated with each comment (e.g., a priority associated with the users, user profiles, and/or user devices that submitted the document comments) (block 910). For example, a CEO may utilize different names or titles depending on the audience of their communication. If a higher ranking attorney (e.g., having a higher priority) indicated that emails using a particular alias (such as an alias not included in the criteria 320) as being responsive as being generated by the CEO, but a lower ranking attorney (e.g., having a lower priority) indicated that such emails were not responsive, the conflict would be resolved in favor of the higher ranking attorney, whereby the merged comments would indicate that emails from the previously-unknown alias should be classified as responsive.) [lower ranking attorney comment ignored or filtered]
to provide a finalised set of comments comprising one or more comments which do not contradict with each other. ([0094] the conflict would be resolved in favor of the higher ranking attorney, whereby the merged comments would indicate that emails from the previously-unknown alias should be classified as responsive. In some such examples, noncontradictory parts of the comments are still included in the merged document comments. For instance, if, in the preceding example, the lower ranking attorney's comment had included additional portions beyond the indication that emails from the CEO were not responsive, the additional portions would be included in the merged comments.)
Regarding Claim 12, Ahmadia and Chapagain disclose all the elements of claim 11,
Chapagain further discloses:further comprising a step of modifying the text by the neural network to provide a revised text based on the finalised set of comments. ([0068] The method 700 also includes: receiving (step 730) a user edit 310 to the document 490; identifying (step 740), by the prompt engine 236, one or more locations within the document 490 that require change based on current content in the document 490 and the user edit; generating (step 750), by the prompt engine 236, one or more second prompts for the large language model 150. The one or more second prompts are generated based on the user edit and correspond to the one or more locations within the document 490.)
The rationale for the combination would be similar to the one already provided earlier.
Regarding Claim 15, Ahmadia and Chapagain disclose all the elements of claim 1,
Ahmadia further discloses: wherein the neural network is a natural language processing (NLP) model or a large language model (LLM). ([0049] Generally, the first generative AI model 125 and the second generative AI model 126 may be large-scale deep neural networks capable of processing and generating media/content such as text, speech, audio, images, videos, etc.) Also see para 0103, generative AI model are LLMs.
Claim 16 is a system claim that corresponds to the method of claim 1, and the rejection and rationale applied in rejection of claim 1 is also applicable.
Claim 17 is recited similarly to claim 6, therefore the similar rationale and grounds of rejection can be applied.
Claim 20 is recited similarly to claim 15, therefore the similar rationale and grounds of rejection can be applied.
Claim 2 is rejected under 35 U.S.C. 103 as being unpatentable over Ahmadia (US 20250258874) in view of Chapagain (US 20250371248), and further in view of Zhao (US 20260064752).
Regarding Claim 2, Ahmadia and Chapagain disclose all the elements of claim 1,
Ahmadia and Chapagain appears to be silent with regards to further comprising a step of providing an explanation as to why the first and second comments are considered to be in contradiction.
Zhao in the related art conflict resolution discloses: further comprising a step of providing an explanation as to why the first and second comments are considered to be in contradiction. ([0069] conflict resolver 112 may determine that first feedback information for the first persona indicates a first value for an attribute of the electronic document that causes a conflict with second feedback information for a second persona. For instance, conflict resolver 112 may determine that a finance persona indicates feedback information requiring a delivery date before a particular date and a technical persona indicates feedback information requiring a delivery date after the particular date.)
Ahmadia/Chapagain/Zhao are considered analogous art. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Ahmadia and Chapagain to combine the teaching of Zhao, because figuring out the reason for the conflict is one of the important steps toward resolving it (Zhao, [0069]).
Claims 8, 9 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Ahmadia (US 20250258874) in view of Chapagain (US 20250371248), and further in view of Wong (US 20250068833).
Regarding Claim 8 Ahmadia/Chapagain disclose all the elements of claim 1,
Ahmadia/Chapagain is silent with regards to: wherein the first comment or the second comment is generated by the neural network based on a comment requirement specified by a user.
Wong in the related field of using LLM to assist with composing discloses: wherein the first comment or the second comment is generated by the neural network based on a comment requirement specified by a user. ([0089] compose generative language model 852 in generating the review (the response). Similarly, flight information could be used in responding to instructions for a rental car or hotel. The browser application 808 may include a settings user interface. The settings user interface may include a menu where users can enable and disable the compose assistant.)
Ahmadia/Chapagain/Wong are considered analogous art. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Ahmadia and Chapagain to combine the teaching of Wong, because LLM can assist user in compose reviews (Wong, [0089]).
Regarding Claim 9, Ahmadia/Chapagain/Wong disclose all the elements of claim 8,
Wong further discloses: wherein the generation of the first comment or the second comment comprises steps of:(i) receiving the comment requirement specified by the user; ([0006] receiving an initial input from a user and determining that the initial input corresponds to a request to generate a document having a document type.)
(ii) wrapping the comment requirement with a second text template to provide a second input prompt; ([0006] generating, by a prompt engine, one or more first prompts for a large language model. The one or more first prompts are generated based on (i) the initial input and (ii) a document template for the document type.)
and (iii) generating, by the neural network, the first comment or the second comment based on the second input prompt. ([0006] receiving first content generated by the large language model based on the one or more first prompts;)
The rationale for the combination would be similar to the one already provided earlier.
Claim 19 is recited similarly to claim 9, therefore the similar rationale and grounds of rejection can be applied.
Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over Ahmadia (US 20250258874) in view of Chapagain (US 20250371248), further in view of Wong (US 20250068833), and furthermore in view of Kuriki (US 20020112006).
Regarding Claim 10, Ahmadia/Chapagain/Wong disclose all the elements of claim 9,
Ahmadia/Chapagain/Wong are silent with regard to: the comment requirement is selected from any one of ([0055] The message type is the information indicating which one of a job request, an investigation, a process of making all of a specific matter fully recognized, requirement for opinions or requests from the members, or the like, is the content of a message. According to the present embodiment, if a message type is selected by a sender when a message is prepared, an attribute such as the requirement for the comment to be included in a response, the requirement for a NO/YES answer or the like, is automatically set according to the thus-selected message type. In the case where the investigation with a time limit, for example, is selected as a message type, attributes of a "requirement for comments", and "with a time limit" are automatically set to the message.) [investigation, job request and etc read on objective]
Ahmadia/Chapagain/Wong/Kuriki are considered analogous art. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Ahmadia/Chapagain/Wong to combine the teaching of Kuriki, because comments can help user decide if they approve of the message (Kuriki, [0013]).
Allowable Subject Matter
Claim 4 is 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.
Regarding claim 4, The closest prior arts found during the search are as follows:
Sano (US 20260288886) teaches extract keyword or phrases and maps them fields, calculates cosine similarities and assign scores.
However, Sano is silent with regards to prefiltering portions of text containing keywords of a comment and it also does not discuss using a neural network to determine portions of comment having highest scores.
Notwithstanding, said aforementioned teachings of prior art cited is respectfully reconsidered and found to fail to teach or fairly suggest either individually or in a reasonable combination the presented limitations in claim 4, as specifically recited.
Potentially Allowable Subject Matter
Claims 13, 14 and 18 would be potentially allowable if amended to overcome the pertinent rejections under section 35 U.S.C. 101. (Claim 13 also needed to overcome 35 U.S.C. 112.)
Regarding claim 13, the closest prior art found is Lee (US 20180267944).
Lee discloses comparing document to the set of revision or edits, and check to determine edit command was applied, but it is silent regarding use of a neural network, comments, and does not explicitly tracking the original document to the edits and the comments.
Notwithstanding, said aforementioned teachings of prior art cited is respectfully reconsidered and found to fail to teach or fairly suggest either individually or in a reasonable combination the presented limitations in claim 13, as specifically recited.
Regarding Claim 14, although slightly different in scope in comparison to claim 13, it also contains similar allowable subject matter.
Notwithstanding, said aforementioned teachings of prior art cited is respectfully reconsidered and found to fail to teach or fairly suggest either individually or in a reasonable combination the presented limitations in claim 14, as specifically recited.
Claim 18 is recited similarly to claim 14, therefore also contains allowable subject matter.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure: Gupta US 20200125658- discloses “receiving a plurality of review comments from each of a plurality of reviewers tasked with reviewing a document; categorizing each of the plurality of review comments into one of a plurality of review topics; identifying a conflict between a first review comment provided by one of the plurality of reviewers and a second review comment provided by another of the plurality of reviewers, wherein the identifying a conflict comprises (i) identifying a sentiment of the first review comment and a sentiment of the second review comment and (ii) determining that the sentiment of the first review comment and the sentiment of the second review comment are different; and generating a question set comprising a plurality of questions based upon a conflict identified for a review comment of the corresponding reviewer, wherein the corresponding reviewer answering the generated question resolves the conflict.” See Abstract and para 0003-0007 and 0020 and fig. 1 for additional details.
Taylor, G. (2024). Integrating AI into Legal Practice. Int'l. In-House Counsel J., 17, 8943.– discloses use of AI in document generation, editing, review. See pages 2-8 for additional details.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Philip H Lam whose telephone number is (571)272-1721. The examiner can normally be reached 9 AM-2 PM Pacific time.
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/PHILIP H LAM/ Examiner, Art Unit 2656
