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
Introduction
This office action is in response to Applicant’s submission filed on 5/20/2024. As such, claims 1-14 and 16-21 have been examined.
Claim Objections
Claim 1-14 and 1-21 are objected to because of the following informalities: in Claims 1, line7. “replacing the text part with an edited version in the at least one edited version to obtain …” should read “replacing the text part with one of the edited versions to obtain…” Appropriate correction is required.
In claim 8, line 12, “replacing the text part with an edited version in the at least one edited version to obtain …” should read “replacing the text part with one of the edited versions to obtain…” Appropriate correction is required.
In claim 16, line 10, “replacing the text part with an edited version in the at least one edited version to obtain …” should read “replacing the text part with one of the edited versions to obtain…” Appropriate correction is required.
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 1-4, 6-11, 13-14, 16-19, and 21 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. Nothing in these claim limitations precludes the steps from practically being performed in the mind. As a whole, claim 1 pertains to keeping the narrative consistent after detecting a change of a sentence and rewriting an edited version, which is a mental process that a human can do. Individually, each of the limitations also pertains to a mental process and/or insignificant extra solution activity, for example:
determining a change to a sentence in the narrative text, wherein an initial context of the sentence before the change is different from a target context of a changed sentence; (e.g., a evaluation/detection step, a human can read a narrative and then reread it to see that a change has been made to the original narrative.)
performing, based on inconsistency between a text part after the sentence in the narrative text and the target context, at least one edit operation on the text part to generate at least one edited version of the text part; (e.g., analysis/judgement of a message, the human checking the narrative and evaluating to determine where portions of the text may contain inconsistencies due to the change in text.)
and replacing the text part with an edited version in the at least one edited version to obtain a rewritten narrative text. (e.g., editing step, the human making some changes to the text to maintain consistency.)
The judicial exception is not integrated into a practical application. In particular, even if the claims imply the use of 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.
Claim 8 recites an electronic device claim that corresponds to the method of claim 1 and is therefore rejected under the same grounds as claim 1 above. While claim 8 further recites a “one processing unit”, “one memory” and “instructions”, 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 8 is not patent eligible.
Claim 16 recites a non-transitory computer-readable storage medium 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 “computer-readable storage medium” and “computer program”, 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 2-4, 6-7, 9-11, 13-14, 17-19 and 21 depend from independent claims 1, 8 and 16 respectively, do not remedy any of the deficiencies of claims 1, 8 and 16 respectively, and therefore are rejected on the same grounds as claims 1, 8 and 16 from above.
Claim 2 further recites: wherein performing the at least one edit operation on the text part to generate the at least one edited version comprises iteratively performing the following operations: determining a causal conflict degree between each of a plurality of text elements in the text part and the target context; (e.g., evaluation/judgment step, the human can identify conflicts and inconsistencies in the text.)
selecting a target text element from the plurality of text elements based on the conflict degree of each of the plurality of text elements, the conflict degree of the target text element being higher than that of a text element not selected from the plurality of text elements; (e.g., evaluation/judgment step, the human can identify the portion of text that contains the highest level of discrepancy/issues from rest of the text.)
and performing a candidate edit operation on the target text element to generate one of the at least one edited version. (e.g., editing step, the human performing editing of the text.) [the human then can repeat the process as needed]
Claim 3 further recite: wherein determining the conflict degree of each of the plurality of text elements comprises: for a corresponding text element in the plurality of text elements, determining a first correlation between the corresponding text element and the target context and a second correlation between the corresponding text element and the initial context using a language model; (e.g., the use of a generic computer component, language model to determine or identify text that doesn’t fit a context, in which the human is also capable of doing.)
and determining the conflict degree of the corresponding text element based on the first correlation and the second correlation. (e.g., the human determining the level of conflict based on the correlations which could be done mentally and with assistance of pen and paper.)
Claim 4 further recites: wherein generating one of the at least one edited version comprises: determining, based on a correlation between a candidate edited version of the text part and the target context and a correlation between the candidate edited version and the initial context, a causal contextual coherence score of the candidate edited version, the candidate edited version being generated by performing the candidate edit operation on the target text element; (e.g., analysis/evaluation step, the human determining correlations of the various variation of the text, and coming up with a contextual coherence score for the edited version of the text.)
determining an acceptance rate of the candidate edited version at least based on the contextual coherence score, the acceptance rate indicating a probability that the candidate edited version is accepted; (e.g., analysis/evaluation step, the human determining how likely the candidate edited version will be accepted.)
and if the acceptance rate exceeds a threshold acceptance rate, determining the candidate edited version as one of the at least one edited version. (e.g., analysis/evaluation step, the human determines if the candidate version is above a threshold, if the version is above the threshold, then accept the change and incorporate changes.)
Claim 6 further recites: wherein replacing the text part with the edited version in the at least one edited version to obtain the rewritten narrative text comprises: determining a causal contextual coherence score of each of the at least one edited version based on a correlation between each of the at least one edited version and the target context and a correlation between each of the at least one edited version and the initial context; (e.g., analysis/judgement step, the human determining a casual contextual coherence score based on various version of text and their respective correlations.)
determining an attribute of each of the at least one edited version that is proportional to the contextual coherence score; (e.g., analysis/judgement step, the human deriving a numerical value or ranking of a edited text version from its coherence score.)
selecting a target version from the at least one edited version based on the attribute of each of the at least one edited version, the attribute of the target version being better than that of aversion not selected from the at least one edited version; (e.g., analysis/judgement step, the human picking or choosing the best version.)
and replacing the text part with the target version to obtain the rewritten narrative text. (e.g., outputting step, the human editing or rewriting the text with the targeted version to create the final version.)
Claim 7 further recites: further comprising: determining a language fluency score of each of the at least one edited version based on a probability of occurrence of each text element in the at least one edited version in the target context, wherein the attribute of each of the at least one edited version is also proportional to the language fluency score. (e.g., analysis/judgement step, the human assessing the text if it reads naturally and/or coherently and free of conflicts/inconsistencies, then assigns a score accordingly.)
Claim 9-11 and 13-14 recites electronic device claims that corresponds to the method of claims 2-4, and 6-7 and are therefore rejected under the same grounds as claims 2-4, and 6-7 from above.
Claim 17-19 and 21 recites CRM claims that corresponds to the method of claims 2-4 and 6, and are therefore rejected under the same grounds as claims 2-4 and 6 from above.
In sum, claims 2-4, 9-11, 13-14, 17-19, and 21 depend from claim 1, 8 and 16, and further recite mental processes as explained above. None of the additional limitations recited in claims 2-4, 9-11, 13-14, 17-19, and 21 amount to anything more than the same or a similar abstract idea as recited in claims 1, 8 and 16. Nor do any limitations in claims 2-4, 9-11, 13-14, 17-19, and 21: (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 2-4, 9-11, 13-14, 17-19, and 21 are not patent eligible.
Claims 5, 12 and 20 appears to contain sufficient details to implement the claim into a practical application and therefore do not fall under abstract ideas and therefore are patent eligible.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1, 8 and 16 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by
Applicant supplied reference, Hao, C., Pang, L., Lan, Y., Wang, Y., Guo, J., & Cheng, X. (2021, May). Sketch and customize: A counterfactual story generator. In Proceedings of the AAAI conference on artificial intelligence (Vol. 35, No. 14, pp. 12955-12962).
Hao discloses 1. A method for rewriting a narrative text, the method comprising: determining a change to a sentence in the narrative text, wherein an initial context of the sentence before the change is different from a target context of a changed sentence; ([pg. 1, right column, first para] As shown in Figure 1, in this dataset, given an entire original story (consisting of a one-sentence premise, a one sentence condition, and a three-sentence ending) and an intervening counterfactual condition, some phrases in the original ending may conflict with the new condition. For example, in the new condition, “she decided to go to the florist” instead of the park. As a result, the place field and the action picked in the original ending should be replaced by some new words to eliminate the conflict.) Also see figs. 1-2, fig. 1 is reproduced below.
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performing, based on inconsistency between a text part after the sentence in the narrative text and the target context, at least one edit operation on the text part to generate at least one edited version of the text part; ([pg. 1, right column, first para] For example, in the new condition, “she decided to go to the florist” instead of the park. As a result, the place field and the action picked in the original ending should be replaced by some new words to eliminate the conflict. To rewrite a counterfactual ending compatible with the given counterfactual condition, an intelligent model should notice the condition changes and revise the conflict words in the original ending properly (field->building and picked->bought in Figure 1).) Also see fig. 1 reproduced above.
and replacing the text part with an edited version in the at least one edited version to obtain a rewritten narrative text. ([pg. 1, right column, first para] For example, in the new condition, “she decided to go to the florist” instead of the park. As a result, the place field and the action picked in the original ending should be replaced by some new words to eliminate the conflict. To rewrite a counterfactual ending compatible with the given counterfactual condition, an intelligent model should notice the condition changes and revise the conflict words in the original ending properly (field->building and picked->bought in Figure 1).) Also see fig. 1 reproduced above.
Regarding Claim 8, Hao discloses: An electronic device, comprising: at least one processing unit; and at least one memory, wherein the at least one memory is coupled to the at least one processing unit, and stores instructions executable by the at least one processing unit, and the instructions, when executed by the at least one processing unit, cause the electronic device to perform the following actions: ([pg. 2, fig. 2 and associated descriptions which discloses a two stage customized model that consist of BERT and GPT2 model which required and implied the use of a computing device, which would inherently contain at least one processing unit, one memory that stores computer program instructions)
As for the rest of the claim, they recite elements from claim 1, and therefore the rationale in rejection applied in rejection of claim 1 is equally applicable.
Regarding Claim 16, Hao discloses: A non-transitory computer-readable storage medium having a computer program stored thereon, wherein the program, when executed by a processor, causes a method for rewriting a narrative text to be implemented, the method comprising: ([pg. 2, fig. 2 and associated descriptions which discloses a two stage customized model that consist of BERT and GPT2 model which required and implied the use of a computing device, which would inherently contain a computer readable storage medium that stores computer program instructions)
As for the rest of the claim, they recite elements from claim 1, and therefore the rationale in rejection applied in rejection of claim 1 is equally applicable.
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.
Claim 2-3, 9-10 and 17-18 are rejected under 35 U.S.C. 103 as being unpatentable over Hao, in view of Dettinger (US 20070112819).
Regarding Claim 2, Hao disclose all of claim 1,
Hao further discloses: wherein performing the at least one edit operation on the text part to generate the at least one edited version comprises iteratively performing the following operations: determining a causal conflict degree between each of a plurality of text elements in the text part and the target context; ([pg. 1, right column, first para] To rewrite a counterfactual ending compatible with the given counterfactual condition, an intelligent model should notice the condition changes and revise the conflict words in the original ending properly (field - >building and picked - >bought in Figure 1).)) [The model identifying conflict words (e.g., field->building and picked->bought) that need revision to align with a new condition (the target context) inherently involves assessing which elements in the original text are causally in conflict with the new condition. The extent of this incompatibility reads on the causal conflict degree.]
selecting a target text element from the plurality of text elements based on the conflict degree of each of the plurality of text elements, the conflict degree of the target text element being higher than that of a text element not selected from the plurality of text elements; (Implies the selection of specific conflicting phrases ([pg. 1, right column, first para] To rewrite a counterfactual ending compatible with the given counterfactual condition, an intelligent model should notice the condition changes and revise the conflict words in the original ending properly (field - >building and picked - >bought in Figure 1).)) [place field and the action picked) that need revision, which prioritizes them for editing over non-conflicting phrases].
and performing a candidate edit operation on the target text element to generate one of the at least one edited version. ([pg. 1, right column, first para] To rewrite a counterfactual ending compatible with the given counterfactual condition, an intelligent model should notice the condition changes and revise the conflict words in the original ending properly (field - >building and picked - >bought in Figure 1).)) [The text explains the revision: field->building and picked->bought in Figure 1, which are the specific edit performed on the target text elements to create the updated, coherent ending.]
Hao does not explicitly disclose iterative process.
Dettinger discloses iterative process ([0046] Turning to FIG. 4, after one or more semantic links has been established, either via block 107 (FIG. 2) or block 207 (FIG. 3), a loop is initiated in block 301 to process each feature in each semantic link to determine whether any calculated or stated feature has a conflicting semantic value, i.e., a semantic inconsistency. If, for a given feature associated with a given semantic link, there are no conflicting values block 301 passes control to block 307 to process the next feature in a semantic link, if one exists. If there is a conflicting semantic value indicating an inconsistency, however, block 301 passes control to block 302 to determine if the conflict is to just be highlighted)
Hao and Dettinger 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 Hao to combine the teaching of Dettinger, because of the significant need continues to exist for a tool capable of assisting authors in maintaining semantic consistency when drafting and revising electronic documents, particularly with regard to linguistic expressions in such documents (Dettinger, [0014]).
Regarding Claim 3, Hao/Dettinger disclose all of claim 2,
Hao further discloses: wherein determining the conflict degree of each of the plurality of text elements comprises: for a corresponding text element in the plurality of text elements, determining a first correlation between the corresponding text element and the target context and a second correlation between the corresponding text element and the initial context using a language model; ([pg. 1, right column, first para] The text describes the need for an intelligent model to notice the condition changes and revise the conflict words, implying a process for identifying conflict. The text refers to an intervening counterfactual condition (target context) that some phrases (text elements) in the original ending (initial context) may conflict with. – which reads on the first correlation. The model must implicitly assess the correlation with this new condition to determine if a conflict exists. Further, the entire original story provides the initial context, and a language model is used to assess the initial compatibility of the text elements before the condition change – which reads on a second correlation. Also see fig. 2 for the structure of the two stage sketch and customized model which reads on the language model.
and determining the conflict degree of the corresponding text element based on the first correlation and the second correlation. ([pg. 1, right column, first para] The text discloses of needing to replace words to eliminate the conflict is a direct application of identifying text elements with a high degree of conflict (i.e., low correlation with the new context, high correlation with the old context).
Claims 9 and 10 are electronic device claim with limitation similar to the limitations of Claims 2 and 3 respectively and are rejected under similar rationale.
Claims 17 and 18 are computer-readable storage medium claim with limitation similar to the limitations of Claims 2 and 3 respectively and are rejected under similar rationale.
Claim 4, 11 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Hao, in view of Dettinger, and further in view of Bliss (US 20210157551)
Regarding Claim 4, Hao/Dettinger disclose all of claim 2,
Hao further discloses: wherein generating one of the at least one edited version comprises: determining, based on a correlation between a candidate edited version of the text part and the target context and a correlation between the candidate edited version and the initial context, a causal contextual coherence score of the candidate edited version, the candidate edited version being generated by performing the candidate edit operation on the target text element; ([pg.2, right col last para to left column first para] A complete story is defined as a five-sentence text {p, c, e}, where the first sentence p is the premise, the second sentence c is the original condition, and the last three sentences constitute the original ending, abbreviated as e. After given a counterfactual condition denoted as cˡ, the task requires to revise the original ending e into a counterfactual ending eˡ which minimally modifies the original one and regains narrative coherency to the counterfactual condition.) [the revised counterfactual ending is e’ – reads on candidate edit version, the counterfactual condition c’ reads on the target context, the original condition c and premise p reads on initial context. The requirement of regain narrative coherency relative to counterfactual condition while minimally modifying the original reads on causal contextual score. The task of revise or replace conflict words in the original ending reads on candidate edit operation.]
Hao/Dettinger does not explicitly disclose the following features.
Bliss discloses: determining an acceptance rate of the candidate edited version at least based on the contextual coherence score, the acceptance rate indicating a probability that the candidate edited version is accepted; ([0062] In an embodiment, the selection logic 410 is configured to compare the score 402 to a threshold value to determine whether the candidate solution design blueprint 306 is accepted or rejected. In some embodiments, the threshold value is manually configured. In other embodiments, the threshold value can be dynamically configured to match an expected acceptance rate. For example, the threshold value can be automatically adjusted such that 30% of the solution design blueprints 306 are accepted. If a historic trend (e.g., 7-day moving average, 30-day moving average, etc.) differs from the expected acceptance rate, then the threshold value can be adjusted up or down to change the likelihood that a given score is above or below the threshold value.)
and if the acceptance rate exceeds a threshold acceptance rate, determining the candidate edited version as one of the at least one edited version. ([0062] In an embodiment, the selection logic 410 is configured to compare the score 402 to a threshold value to determine whether the candidate solution design blueprint 306 is accepted or rejected.)
Hao/Dettinger/Bliss 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 Hao/Dettinger to combine the teaching of Bliss, because improved accuracy, relevance and consistency in acceptance rate for the candidate result can be automatically assessed (Bliss, [0062]).
Claim 11 is electronic device claim with limitation similar to the limitations of Claim 4 and are rejected under similar rationale.
Claim 19 is computer-readable storage medium claim with limitation similar to the limitations of Claims 4 and are rejected under similar rationale.
Claim 6, 13 and 21 are rejected under 35 U.S.C. 103 as being unpatentable over Hao, in view of Perez (US 20170177716).
Regarding Claim 6, Hao disclose all of claim 1,
Hao further discloses: wherein replacing the text part with the edited version in the at least one edited version to obtain the rewritten narrative text comprises: determining a causal contextual coherence score of each of the at least one edited version based on a correlation between each of the at least one edited version and the target context and a correlation between each of the at least one edited version and the initial context; ([pg.2, right col last para to left column first para] A complete story is defined as a five-sentence text {p, c, e}, where the first sentence p is the premise, the second sentence c is the original condition, and the last three sentences constitute the original ending, abbreviated as e. After given a counterfactual condition denoted as cˡ, the task requires to revise the original ending e into a counterfactual ending eˡ which minimally modifies the original one and regains narrative coherency to the counterfactual condition.) [the revised counterfactual ending is e’ – reads on candidate edit version, the counterfactual condition c’ reads on the target context, the original condition c and premise p reads on initial context. The requirement of regain narrative coherency relative to counterfactual condition while minimally modifying the original reads on causal contextual score. The task of revise or replace conflict words in the original ending reads on candidate edit operation.]
and replacing the text part with the target version to obtain the rewritten narrative text. ([pg. 1, right column, first para] For example, in the new condition, “she decided to go to the florist” instead of the park. As a result, the place field and the action picked in the original ending should be replaced by some new words to eliminate the conflict. To rewrite a counterfactual ending compatible with the given counterfactual condition, an intelligent model should notice the condition changes and revise the conflict words in the original ending properly (field->building and picked->bought in Figure 1).) Also see fig. 1 reproduced above.
Hao does not disclose the below features.
Perez discloses: determining an attribute of each of the at least one edited version that is proportional to the contextual coherence score; ([0042] wherein the dialogue move selection module is further to determine, based on the dialogue history, a plurality of dialogue coherence scores, wherein each dialogue coherence score of the plurality of dialogue coherence scores corresponds to a semantic interpretation candidate of the plurality of semantic interpretation candidates, wherein each dialogue coherence score of the plurality of dialogue coherence scores is indicative of a dialogue coherence of the corresponding semantic interpretation candidate with the dialogue history, and wherein the dialogue move selection module is to rank each semantic interpretation candidate of the plurality of semantic interpretation candidates further based on the plurality of dialogue coherence scores of the plurality of semantic interpretation candidates.) [the rank or selection is based directly on the score, the higher the score, the higher the rank]
selecting a target version from the at least one edited version based on the attribute of each of the at least one edited version, the attribute of the target version being better than that of aversion not selected from the at least one edited version; ([0042] rank each semantic interpretation candidate of the plurality of semantic interpretation candidates further based on the plurality of dialogue coherence scores of the plurality of semantic interpretation candidates.)
Hao and Perez 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 Hao to combine the teaching of Perez, because the method discloses use contextual coherence to improve selection of the best interpretation of the user’s input (Perez, [0042]).
Claim 13 is electronic device claim with limitation similar to the limitations of Claim 6 and are rejected under similar rationale.
Claim 21 is computer-readable storage medium claim with limitation similar to the limitations of Claims 6 and are rejected under similar rationale.
Claims 7 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Hao, in view of Perez, and further in view of Freitag (US 20220215184).
Regarding Claim 7, Hao/Perez disclose all of claim 6,
Hao/Perez does not explicitly disclose the following feature.
Freitag discloses: determining a language fluency score of each of the at least one edited version based on a probability of occurrence of each text element in the at least one edited version in the target context, wherein the attribute of each of the at least one edited version is also proportional to the language fluency score. ([0060] At block 806, the system processes the selected instance of text to determine a corresponding ALM score. For example, the system can determine a fluency score as well as a semantics score corresponding to the selected instance of text. Additionally or alternatively, the system can determine an ALM score based on the determined fluency score and semantics score. Determining an ALM score corresponding with an instance of text is described with respect to process 700 of FIG. 7.) Also see para 0094, determining a conditional probability indicating a likelihood that the instance of natural language text was generated using the set of structured data.)[the text discloses process of taking an edited instance, calculating a fluency score along with a semantic score and using that to define an ALM score which reads on the attribute.]
Hao/Perez/Freitag 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 Hao/Perez to combine the teaching of Freitag, because the method discloses would improve user experience to ensure that the generated text is easy for the user to read and understand (Freitag, [0060]).
Claim 14 is electronic device claim with limitation similar to the limitations of Claim 7 and are rejected under similar rationale.
Allowable Subject Matter
Claims 5, 12 and 20 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
The following is a statement of reasons for the indication of potentially allowable subject matter:
With respect to Claim 5, Hao teaches contextual coherence score and candidate edit version, see pg. 1, right column, first para, and Dettinger teaches acceptance rate of the candidate edit version, see para 0046, and although Gao US 20210117625 teaches logical representation which would read on language fluency score, and semantic confidence for given logical representation and further teaches performing exponential transformation, see para 0090. However, the combination of reference still short of disclosing “… determining the acceptance rate based on the contextual coherence score, the language fluency score, and the transformation probability.”
Although in different statutory categories, claims 12 and 20 are similarity recited as claim 5, therefore the same rationale can be applied to these claims.
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 claims 5, 12 and 20, as specifically recited.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Vinay (US 20190251150) discloses a method/system for updating digital documents while maintaining consistency with other portions of the document through the use of trailing changes. See para 0048, and figs 1-4 for additional details.
Qin, L., Bosselut, A., Holtzman, A., Bhagavatula, C., Clark, E., & Choi, Y. (2019). Counterfactual story reasoning and generation. arXiv preprint arXiv:1909.04076. -discloses generating text via counterfactual story reasoning. See Abstract, sections 3-5, figs 1-2, and table 1 for additional details.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Phillip H Lam whose telephone number is (571)272-1721. The examiner can normally be reached 9 AM-5 PM Pacific Time.
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/PHILIP H LAM/ Examiner, Art Unit 2656