DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendment
In response to the Office Action mailed May 5, 2026, applicant submitted an amendment filed on August 5, 2026, in which the applicant amended and requested reconsideration.
Response to Arguments
Applicants argue that the prior art cited fails to teach the claims as amended. Applicants’ arguments are persuasive but are moot in view of new grounds of rejection.
Terminal Disclaimer
The application/patent being disclaimed has been improperly identified since the number used to identify the application being disclaimed is incorrect. The slash between the prior patent number needs to be deleted. Therefore, the Terminal Disclaimer has not been approved.
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 conflicting claims 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); 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 nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) 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 www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1, 3, 6-8, 10, 13-15, 17 and 20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1, 9-10, 12 and 20 of U.S. Patent No.12/039,798. Although the claims at issue are not identical, they are not patentably distinct from each other because
Current application 18/746,820
Parent Application now PN 12/039,798
Regarding claims 1, 8 and 15, Gao discloses a method, apparatus and a non-transitory computer-readable medium, hereinafter referenced as a method for data processing, comprising:
one or more memories storing processor-executable code; and one or more processors coupled with the one or more memories and individually or collectively operable to execute the code comprising:
receiving a query input comprising an input document and a natural language query, the input document including a plurality of input text fields, wherein at least one input text field comprises a key value pair at a first two-dimensional location within the input document, and wherein the natural language query indicates a request for a value associated with a key in the input document;
identifying, based at least in part on processing the natural language query of the query input, an input key phrase that corresponds with the key and is derived from the natural language query of the query input, the input key phrase requesting the value associated with the key indicated via the natural language query; and
selecting, by performing an optical character recognition process a character string at a second two-dimensional location in the input document as the value of the key that corresponds with the input key phrase, wherein the selecting is based at least in part on inputting the input key phrase and output of the optical character recognition process into a machine learned model trained using a plurality of two-dimensional locations in a plurality of input files with a plurality of input file formats, wherein the machine learned model is trained to extract information from fixed forms and non-fixed forms.
Regarding claims 1, 12 and 20, Gao discloses a method, apparatus and a non-transitory computer-readable medium, hereinafter referenced as a method for data processing, comprising: receiving an input document including a plurality of input text fields; receiving an input key phrase querying a value for a key-value pair that corresponds to one or more of the plurality of input text fields; extracting, using an optical character recognition model, a set of character strings and a set of two-dimensional locations of the set of character strings on a layout of the input document; inputting the extracted set of character strings, the set of two-dimensional locations, and the input key phrase into a machine learned model that is trained to compute a set of probabilities for the set of character strings corresponding to the value for the key-value pair corresponding to the input key phrase; identifying that a character string of the set of character strings corresponds to the value for the key-value pair corresponding to the input key phrase based at least in part on the inputting and on a respective probability for the character string being the value corresponding to the input key phrase being greater than one or more other respective probabilities of one or more other character strings of the set of character strings; and transmitting the identified value corresponding to the input key phrase.
Regarding claims 3, 10 and 17, Gao discloses a method wherein selecting the character string comprises: extracting the two-dimensional location in the input document based at least in part on the character string being associated with the value of the key that corresponds with the input key phrase.
Regarding claims 1, 12 and 20, Gao discloses a method comprising: inputting the extracted set of character strings, the set of two-dimensional locations, and the input key phrase into a machine learned model that is trained to compute a set of probabilities for the set of character strings corresponding to the value for the key-value pair corresponding to the input key phrase.
Regarding claims 6, 13 and 20, Gao discloses a method further comprising: training the machine learned model based at least in part on inputting the plurality of input file formats into the machine learned model.
Regarding claim 9, Gao discloses a method further comprising: training the machine learned model based at least in part on inputting a plurality of input file formats into the machine learned model.
Regarding claims 7 and 14, Gao discloses a method wherein the input document comprises a fixed form, a non-fixed form, or both.
Regarding claim 10, Gao discloses a method wherein the input document comprises a fixed form, a non-fixed form, or both.
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(s) 1, 3-4, 6-8, 10-11, 13-15, 17-18 and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Duta (PGPUB 2020/0117944) in view of Mathew et al. (DocVQA: A dataset for VQA on Document Images), hereinafter referenced as Mathew.
Regarding claims 1, 8 and 15, Duta discloses method, apparatus and a non-transitory computer-readable medium, hereinafter referenced as a method for data processing, comprising:
receiving a query input comprising an input document (document), the input document including a plurality of input text fields (processing forms containing structured information including invoices, receipts, purchase requests, tax forms, etc. wherein the forms contain key-value pairs; p. 0001, 0008, 0031), wherein at least one input text field comprises a key value pair at a first two-dimensional location within the input document (x, y coordinate; p. 0060-0078), and
identifying, based on query, an input key phrase that corresponds with the key and is derived from the query of the query input, the input key phrase requesting the value associated with the key indicated (key value; p. 0027-0037)
selecting, by performing an optical character recognition process a character string at a second two-dimensional location in the input document as the value of the key that corresponds with the input key phrase (OCRs documents to identify characters and locations; p. 0010, 0025), wherein the selecting is based at least in part on inputting the input key phrase and output of the optical character recognition process into a machine learned model trained using a plurality of two-dimensional locations in a plurality of input files with a plurality of input file formats (x, y coordinate; p. 0012, 0060-0078), wherein the machine learned model is trained to extract information from fixed forms and non-fixed forms (system learns the keys from different types of forms and can then extract values for the keys; p. 0008-0009), but does not specifically teach wherein the natural language query indicates a request for a value associated with a key in the input document.
Mathew discloses a method comprising:
identifying, based at least in part on processing the natural language query of the query input, an input key phrase that corresponds with the key and is derived from the natural language query of the query input, the input key phrase requesting the value associated with the key indicated via the natural language query (receives a document image and a natural language question and generates an answer by interpreting the document. The answer may be a word token appearing in a document. The extracted information structured as key-value relationships; Introduction and section 2), to identify the corresponding information within the document.
Therefore, it would have been obvious to one of ordinary skill of the art, before the effective filing date of the claimed invention, to modify the method as described above, to thereby permit retrieval of requested value without requiring the user to know the documents particular layout or location of the requested information.
Regarding claims 3, 10 and 17, Duta discloses a method wherein selecting the character string comprises:
extracting the second two-dimensional location (two-dimensional) in the input document based at least in part on the character string being associated with the value of the key that corresponds with the input key phrase (x, y coordinate; p. 0012, 0060-0078).
Regarding claims 4, 11 and 18, Duta discloses a confidence score for the extracted values which can be determined and low confidence score is filtered (p. 0047-0049). In addition, Mathew discloses generating a probability score for the character string associated with the value of the key that corresponds with the input key phrase, wherein selecting the character string is based at least in part on the probability score of the character string (evaluates trained models from the documents OCR tokens. The LoRRA baseline uses an output mechanism that can wither predict an answer from a fixed vocabulary or copy an answer from a dynamic vocabulary comprising the OCR tokens in the document image/BERT; sections 3.2, 4.2-4.3, 5.3).
Regarding claims 6, 13 and 20, Duta discloses a method further comprising:
training the machine learned model based at least in part on inputting the plurality of input file formats into the machine learned model (system learns the keys from different types of forms and can then extract values for the keys; p. 0008-0009).
Regarding claims 7 and 14, Duta discloses a method wherein the input document comprises a fixed form, a non-fixed form, or both (structured/unstructured documents, system learns the keys from different types of forms and can then extract values for the keys; p. 0008-0009).
Claim(s) 5, 12 and 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Duta in view of Mathew and in further view of Rodriguez-Serrano et al. (PGPUB 2014/0355835), hereinafter referenced as Rodriguez-Serrano.
Regarding claims 5, 12 and 19, Duta in view of Mathew discloses a method as described above, but does not specifically teach a method wherein selecting the character string is based at least in part on the probability score for the character string and a ranking of the probability score for the character string.
Rodriguez-Serrano discloses a method wherein selecting the character string is based at least in part on the probability score for the character string and a ranking of the probability score for the character string (alternative OCR text strings, OCR confidence scores are ranked and the highest ranking OCR string is treated as the OCR result and may re-rank candidates; p. 0044, 0103-0105, 0132-0134), to evaluate competing OCR recognition results.
Therefore, it would have been obvious to one of ordinary skill of the art, before the effective filing date of the claimed invention, to identify the best results.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. This information has been detailed in the PTO 892 attached (Notice of References Cited).
Perronnin teaches a dialog system for comprehension evaluation.
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JAKIEDA R JACKSON whose telephone number is (571)272-7619. The examiner can normally be reached Mon - Fri 6:30a-2:30p.
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, Daniel Washburn can be reached at 571.272.5551. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/JAKIEDA R JACKSON/Primary Examiner, Art Unit 2657
Prosecution Insights