Introduction
1. This office action is in response to Applicant’s submission filed on 6/25/2026. Claims 1-20 are pending in the application and have been examined.
Notice of Pre-AIA or AIA Status
2. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Information Disclosure Statement
3. The information disclosure statement (IDS) submitted on 9/18/2026 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Response to Arguments
4. The Amendment filed 6/25/2026 has been entered and fully considered. With regard to the rejections under 35 USC 101, the arguments and amendments presented are found persuasive and those rejections are withdrawn. With regard to the rejections under 35 USC 103, some of the arguments presented are rendered moot by the new rejections based on US Pat. App. Pub. No. 20080319735 (Kambhatla et al., hereinafter “Kam”). Please note, at least the subject matter of “the first target phrase comprising a first verb” was not previously considered, and has been added to Claim 1. Accordingly, this action is made final.
Claim Rejections - 35 USC § 103
5. 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 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.
6. Claims 1-7, 11-16, 19, and 20 are rejected under 35 U.S.C. 103 as unpatentable over US Pat. App. Pub. No. 20210133251 (Tiwary et al., hereinafter “Tiwary”) in view of US Pat. App. Pub. No. 20040030540 (Ovil et al., hereinafter “Ovil”) and US Pat. App. Pub. No. 20080319735 (Kambhatla et al., hereinafter “Kam”).
With regard to Claim 1, Tiwary describes:
“One or more non-transitory computer-readable media comprising instructions that, when executed by one or more hardware processors, cause performance of operations comprising:
identifying a first target phrase of a content item, [[the first target phrase comprising a first verb]]; (Paragraph 60 describes that phrases are identified that may be replaced with paraphrases.)
selecting a first subset of characters of a first verb, comprised within the first target phrase, for comparison with a plurality of nouns extracted from a data corpus for a phrase conversion process; (Paragraph 60 describes that potential replacement phrases are extracted from a corpus and included in a database.)
comparing the first subset of characters, of the first verb, to the plurality of nouns; (Paragraph 70 describes that verb phrases are identified for replacement.)
identifying a first candidate subset of one or more nouns, of the plurality of nouns, that includes a sequence of characters that match the first subset of characters of the first verb; (Paragraphs 65 and 66 describe that a list of replacement phrases are selected based on similarity to the phrase to be replaced.)
selecting a particular noun, of the first candidate subset of one or more nouns, [[based on on at least one of (a) the first association between the first industry and the first verb as determined by the machine learning model or (b) a frequency associated with the particular noun within the data corpus]]; (Paragraph 72 describes that one of the candidates is selected.) and
converting the first target phrase of the content item to a first standard phrase at least by replacing the first verb within the first target phrase with the particular noun. (Paragraph 72 describes that the selected candidate is used to replace the original phrase.)
Tiwary does not explicitly describe that the selection is based on a frequency associated with the particular noun within the data corpus, or
“the first target phrase comprising a first verb;
obtaining one or more training datasets for training a machine learning model,
a training dataset of the one or more training datasets comprising a particular content item and an industry associated with the particular content item, the particular content item comprising a set of one or more verbs;
training the machine learning model based on the training datasets to predict industries associated with verbs;
applying the machine learning model to the first verb to predict the industry associated with the first verb.”
However, paragraph 115 of Ovil describes that the usage frequency in a corpus may be used as a selection criteria for replacing words/phrases.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include the frequency usage selection as described by Ovil into the method of Tiwary to improve the language enhancement, as described in paragraph 115 of Ovil.
Tiwary in view of Ovil does not explicitly describe
“the first target phrase comprising a first verb;
obtaining one or more training datasets for training a machine learning model,
a training dataset of the one or more training datasets comprising a particular content item and an industry associated with the particular content item, the particular content item comprising a set of one or more verbs;
training the machine learning model based on the training datasets to predict industries associated with verbs;
applying the machine learning model to the first verb to predict the industry associated with the first verb.”
However, Kam describes:
“the first target phrase comprising a first verb; (Paragraphs 12 and 13 describe that potential target words are verbs.)
obtaining one or more training datasets for training a machine learning model,
a training dataset of the one or more training datasets comprising a particular content item and an industry associated with the particular content item, the particular content item comprising a set of one or more verbs; (Paragraph 12 describes that a training set can be a set of pairs of verbs and verb arguments. Paragraphs 13-23 describe that there can be many arguments associated with the verb “offer,” some of which are referring to entities that can be considered “an industry.” In particular, ARG0 in paragraphs 19 and 20 refer to industries)
training the machine learning model based on the training datasets to predict industries associated with verbs; (Paragraph 48 describes that the model is trained with the data set during a training phase.)
applying the machine learning model to the first verb to predict the industry associated with the first verb.” (Paragraph 47 describes that the trained model is used to predict semantic role labels for the arguments of particular verbs. Paragraphs 19 and 20 include labels that are industries.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include the training method as described by Kam into the method of Tiwary in view of Ovil to allow the model to predict semantic role labels of the target verbs, as described in paragraph 47 of Kam.
With regard to Claim 2, Tiwary describes “prior to selecting the first subset of characters of the first verb, selecting the first verb for the phrase conversion process responsive to determining that the first verb is positioned as an initial word or final word of the first target phrase.” Paragraph 59 describes that the “phrase” being replaced may be a single word, which would make it the first and last word in the phrase.
With regard to Claim 3, Tiwary describes “selecting a number of characters to include in the first subset of characters based on a total number of characters in the first verb and a target percentage value to be applied to the total number of characters.” Paragraph 59 describes that one word can be entirely replaced. Thus, it purposefully selects 100% of the word to be replaced.
With regard to Claim 4, Tiwary in view of Ovil does not explicitly describe this feature. However, Kam describes “the particular noun is selected based further on an industry associated with the first verb.” Paragraph 47 of Kam describes that the trained model is used to predict semantic role labels for the arguments of particular verbs. Paragraphs 19 and 20 of Kam include labels that are industries.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include the training method as described by Kam into the method of Tiwary in view of Ovil to allow the model to predict semantic role labels of the target verbs, as described in paragraph 47 of Kam.
With regard to Claim 5, Tiwary describes “the first target phrase is converted to the first standard phrase further by reordering a set of words within the first target phrase, after replacing the first verb within the first target phrase with the particular noun, based on a standard phrase structure.” Example 3 in Figure 8 shows that “change your payment method” can be changed to “payment method amendment,” which includes reordering the phrase after changing the verb to a noun.
With regard to Claim 6, Tiwary describes “the standard phrase structure defines a positioning of a preposition type relative to a noun type, and wherein reordering the set of words within the first target phrase comprises reordering a preposition and a noun within the set of words in accordance with the positioning of the preposition type relative to the noun type in the standard phrase structure.” Example 3 in Figure 8 shows that “change your payment method” can be changed to “payment method amendment,” which includes reordering the phrase originally including a preposition after changing the verb to a noun.
With regard to Claim 7, Tiwary describes “identifying a second target phrase of the content item; (Paragraph 60 describes that phrases are identified that may be replaced with paraphrases.)
selecting a second subset of characters of a second verb, comprised within the second target phrase, for comparison with the plurality of nouns for the phrase conversion process; (Paragraph 60 describes that potential replacement phrases are extracted from a corpus and included in a database.)
comparing the second subset of characters of the second verb with the first subset of characters of the first verb; (Paragraph 70 describes that verb phrases are identified for replacement.)
determining that the second subset of characters is identical to the first subset of characters; (Paragraphs 65 and 66 describe that a list of replacement phrases are selected based on similarity to the phrase to be replaced.) and
converting the second target phrase of the content item to a second standard phrase at least by replacing the second verb within the second target phrase with the particular noun. (Paragraph 72 describes that one of the candidates is selected.)
With respect to Claims 11-16, non-transitory computer readable media Claim 1 and method Claim 11 are related as a non-transitory storage media programmed to perform the same method, with each claimed non-transitory storage media function corresponding to each claimed method step. Accordingly, Claims 11-16 are similarly rejected under the same rationale as applied above with respect to Claims 1, 2, 4, 5, 6, and 7, respectively.
With respect to Claim 20, system Claim 20 and non-transitory computer readable media Claim 1 are related as a system programmed to perform the same method as performed by the non-transitory computer readable media, with each claimed system function corresponding to each claimed non-transitory computer readable media method step. Accordingly, Claim 20 is similarly rejected under the same rationale as applied above with respect to Claim 1.
7. Claims 10 and 19 are rejected under 35 U.S.C. 103 as unpatentable over Tiwary in view of Ovil and Kam and further in view of US Pat. No. 5,371,676 (Heemels et al., hereinafter “Heemels”).
With regard to Claims 10 and 19, Tiwary in view of Ovil and Kam does not explicitly describe this subject matter. However, column 3, line 42 to column 4, line 63 of Heemels describes searching for a word in a list of words using a binary search algorithm.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include the binary search algorithm as described by Heemels into the method of Tiwary in view of Ovil and Kam to improve the search performance, as described at column 3, line 42 to column 4, line 63 of Heemels.
Allowable Subject Matter
8. Claims 8, 9, 17, and 18 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 and to overcome the rejection under 35 USC 101.
The art of record does not teach or suggest:
“identifying a plurality of target phrases of the content item;
identifying a plurality of verbs comprised respectively within the plurality of target phrases;
sorting the plurality of verbs in a first alphabetical order; and
sorting the plurality of nouns in a second alphabetical order;
subsequent to selecting the particular noun:
selecting a second subset of characters of a second verb that is subsequent to the first verb in the first alphabetical order; and
comparing the second subset of characters of the second verb to a subset of the plurality of nouns, wherein the subset of the plurality of nouns comprises nouns subsequent to the particular noun in the second alphabetical order” as recited in Claims 8 and 17.
Conclusion
9. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
“Drug Disease Relation Extraction from Biomedical Literature Using NLP and Machine Learning” (Karaa et al.) describes a neural network that determines relationships between text entities.
10. Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
11. Any inquiry concerning this communication or earlier communications from the examiner should be directed to EDWARD TRACY whose telephone number is (571)272-8332. The examiner can normally be reached Monday-Friday 9 AM- 5PM.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Bhavesh Mehta can be reached on 571-272-7453. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/EDWARD TRACY JR./Examiner, Art Unit 2656
/BHAVESH M MEHTA/Supervisory Patent Examiner, Art Unit 2656
