DETAILED ACTION
1. This is a Final Office Action Correspondence in response to U.S. Application No. 18/944474 filed on January 30, 2026.
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 .
Response to Arguments
3. The Applicant’s arguments have been considered but are not persuasive.
On Pg. 8 of remarks in regards to 35 U.S.C. 103, relating to claim 1, Applicant “To support its assertion, the Office Action cites to Lightner, 6:48-52, which describes extracting "entities" from a search query, and treating those extracted entities as items of interest for indexing and co-occurrence analysis, i.e., "to extract and disambiguate as many entities as possible." However, an entity is not analogous to the claimed attributes that are extracted from the received information. Indeed, independent claim 15 requires "receive information comprising multiple versions of data associated with an entity of a plurality of entities... extract... and store in an entity database, one or more attributes" (emphasis added). That is, attributes may be thought of as, e.g., characteristics/properties/fields of or associated with an entity, but an entity is not an attribute. Even if, in arguendo, the interpretation of "entity" in Lightner was stretched to encompass something like a property or characteristic, Lightner still fails to teach or suggest the per-attribute requirements to create and store a set of timeslice objects, and the association of different values of the attribute with different timeslice objects.”
Examiner replies that Lightner does teach this claimed concept. Col. 6 Lines 47-53 Lightner discloses the concept of extracting features from the content.
Pg. 8 of remarks in regards to 35 U.S.C. 103, relating to claim 1, Applicant “The Office Action further acknowledges that the alleged combination of Osesina and
Lightner fail to teach or suggest independent claim 15's requirement to "create and store a set of timeslice objects for each of the one or more attributes." However, the Office Action asserts that Charnock cures this deficiency of Osesina and Lightner. Applicant disagrees. First, Charnock, [0090] describes the contents of an "internal knowledgebase" backing an inferencing component, referencing, e.g., groups of interest, members, countermeasures, events, symbolic objects, and empirically measured propagation times. Charnock, [0090] is silent as to "timeslice objects," as well as to creating and storing a set of objects per attribute”.
Examiner replies that Lightner does teach this claimed concept. Col. 6 Lines 47-53 Lightner discloses the concept of extracting features from the content.
Pg. 9 of remarks in regards to 35 U.S.C. 103, relating to claim 1, Applicant “There does not appear to be any [0533] paragraph in Charnock. The only mention of "merging" appears to be the merging of a new sketch with an existing sketch at [0293], [0295], or the merging of an unrelated image component into a LIC at [0298]. The only mention of overlap in Charnock appears to be regarding overlapping demographic groups at [0063], an acknowledgement that information in a knowledgebase likely includes overlap at [0174], overlapping zones in images at [0382], and a user selecting/dragging actors or images onto a canvas for known/probable overlap at [0394]. However, none of these teachings or references in Charnock read on "overlapping durations of respective timeslice objects," let alone comparing them. Accordingly, nothing in Charnock appears to teach or suggest the combination of timeslice objects (that correspond to the same entity, which is determined at least in part by the comparison of overlapping durations) into a single entity”.
Examiner replies that Charnock does teach this claimed concept. Par. 0285 Charnock discloses data objects at different times may be collated in order to populate an event.
Claim Rejections - 35 USC § 103
4. 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 (i.e., changing from AIA to pre-AIA ) 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.
5. 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. Claim(s) 15, 16, 17 and 24-26 is/are rejected under 35 U.S.C. 103 as being unpatentable over Osesina U.S. Patent No. 10,997,134 (herein as ‘Osesina’) and further in view of Lightner et al. U.S. Patent No. 9,619,571 (herein as ‘Lightner’) and Charnock et al. U.S. Patent Application Publication No. 2021/0174128 (herein as ‘Charnock’).
As to claim 15 a system, comprising: a processor; and a memory comprising instructions that when executed, cause the processor to ([ "Entity resolution {i:e.~ record linkage} involves the analysis/discovering of datasets that refer to the same real world entity." {Osesina: Abstract}]:
receive information comprising multiple versions of data associated with an entity of a plurality of entities (Col. 11 Lines 60-63 Osesina discloses in step S104 as input, a plurality of records are received that are known to be associated with a same individual Each record includes a plurality of fields containing data. Col. 9 Lines 41-46 Osesina discloses a plurality of records are received by the entity resolution device 100 from the database 300 in cooperation with the controller 104~ memory 10~ J/O interface 12~ and storage 112-the records known to be associated with a same individual);
Osesina does not teach but Lightner teaches extract from the received information, and store in an entity database, one or more attributes (Col. 6 Lines 48-52 Lightner discloses during the extraction one or more feature recognition and extraction algorithms may be employed Also, a score may be assigned to each extracted feature indicating the level of certainty of the feature being correctly extracted with the correct attributes);
Osesina and Lightner are analogous art because they are in the same field of endeavor, attribute processing. It would have been obvious to one of ordinary skill in the art, before the effective filing date, to modify the identifying of records of Osesina to include the extracting attributes of Lightner, to allow for retrieval of relevant documents. The suggestion/motivation to combine is that it would be obvious to try in order to retrieve relevant documents (Col. 1 Lines 40-47 Lightner).
Osesina in combination with Lightner does not teach but Charnock teaches create and store a set of timeslice objects for each of the one or more attributes (Par. 0090 Charnock discloses identifying the objects associated with the time);
predict whether at least a subset of the set of timeslice objects corresponds to the same entity of the plurality of entities by comparing overlapping durations of respective timeslice objects using a machine-learning similarity model and responsive to predicting that the subset of timeslice objects correspond to the same entity of the plurality of entities, combine the subset of timeslice objects into a single entity identity record to generate an unambiguous entity database (Par. 0285 Charnock discloses data objected at different times may be collated in order to populate an event. Par. 0394 Charnoack discloses and drag objects onto a canvas to query the system for any known or probable overlap or intersection among all of them or any subset of them).
Osesina and Charnock are analogous art because they are in the same field of endeavor, attribute processing. It would have been obvious to one of ordinary skill in the art, before the effective filing date, to modify the identifying of records of Osesina to include creating data structures of Charnock, to allow for retrieval of relevant documents. The suggestion/motivation to combine is that it would be obvious to try in order to gather relevant data quickly (Par. 0017-0018 Charnock).
As to claim 16 Osesina in combination with Lightner and Charnock teaches each and every limitation of claim 15.
In addition Charnock teaches wherein the instructions that when executed cause the processor to extract the one or more attributes, further cause the processor to: tokenize the received information; responsive to identifying that the received information has multiple components based on one or more tokens (Par. 0142 Charnock discloses associating the data with the tokens);
determine that the one or more attributes are related to a name of the entity based on the multiple components; and disambiguate and classify the multiple components into at least a base name, a connector, a function and/or industry, and a legal identifier associated with the entity name (Col. 6 Lines 15-25 Osesina discloses labeling the documents).
As to claim 17 Osesina in combination with Lightner and Charnock teaches each and every limitation of claim 16.
In addition Osesina teaches wherein the instructions that when executed cause the processor to extract the one or more attributes, further cause the processor to: responsive to identifying that a first attribute of the one or more attributes is a location: disambiguate and compare one or more tokens associated with the location with a plurality of known locations; responsive to determining that there is a match between the one or more tokens associated with the location and a first known location of the plurality of locations, assign a geocode to the location (Col. 10 Lines 20-27 Osesina discloses the unknown data is associated with multiple records. Col. 11 Lines 30-46 Osesina discloses labeling the data).
As to claim 24 Osesian teaches a method, comprising:
extracting and storing at an entity database, by an entity disambiguation computer, one or more attributes from information received from one or more external data sources (Col. 6 Lines 48-52 Lightner discloses during the extraction one or more feature recognition and extraction algorithms may be employed Also, a score may be assigned to each extracted feature indicating the level of certainty of the feature being correctly extracted with the correct attributes);
Osesina and Lightner are analogous art because they are in the same field of endeavor, attribute processing. It would have been obvious to one of ordinary skill in the art, before the effective filing date, to modify the identifying of records of Osesina to include the extracting attributes of Lightner, to allow for retrieval of relevant documents. The suggestion/motivation to combine is that it would be obvious to try in order to retrieve relevant documents (Col. 1 Lines 40-47 Lightner).
Osesina in combination with Lightner does not teach but Charnock teaches storing and associating each of the one or more attributes with a timeslice object, wherein attributes of the one or more attributes having different values are associated with different timeslice objects (Par. 0090 Charnock discloses identifying the objects associated with the time);
selecting an attribute pair of the one or more attributes, and comparing attributes of the attribute pair based on start and end times associated with corresponding timeslice objects; predicting whether the attribute pair corresponds to a same entity based on the comparison of the attributes and disambiguating the entity database by merging the attributes of the attribute pair pursuant to a prediction that the attribute pair corresponds to the same entity (Par. 0285 Charnock discloses data objected at different times may be collated in order to populate an event. Par. 0394 Charnock discloses and drag objects onto a canvas to query the system for any known or probable overlap or intersection among all of them or any subset of them. Par. 0096 Charnock disclose using the deep learning process to identify new types of transformations that is now on the radar but different enough to not be trapped by the standard feature);
Osesina and Charnock are analogous art because they are in the same field of endeavor, attribute processing. It would have been obvious to one of ordinary skill in the art, before the effective filing date, to modify the identifying of records of Osesina to include creating data structures of Charnock, to allow for retrieval of relevant documents. The suggestion/motivation to combine is that it would be obvious to try in order to gather relevant data quickly (Par. 0017-0018 Charnock).
As to claim 25 Osesina in combination with Lightner and Charnock teaches each and every limitation of claim 24.
In addition Charnock teaches further comprising: tokenizing the information; responsive to identifying that the information has multiple components based on one or more tokens: determining that the one or more attributes are related to a name of the entity based on the multiple components (Par. 0142 Charnock discloses associating the data with the tokens);
and disambiguating and classifying the multiple components into at least a base name, a connector, a function and/or industry, and a legal identifier associated with the entity name (Col. 6 Lines 15-25 Osesina discloses labeling the documents).
As to claim 26 Osesina in combination with Lightner and Charnock teaches each and every limitation of claim 25.
In addition Osesina teaches further comprising: responsive to identifying that a first attribute of the one or more attributes is a location: disambiguating and comparing one or more tokens associated with the location with a plurality of known locations; responsive to determining that there is a match between the one or more tokens associated with the location and a first known location of the plurality of locations, assigning a geocode to the location (Col. 10 Lines 20-27 Osesina discloses the unknown data is associated with multiple records. Col. 11 Lines 30-46 Osesina discloses labeling the data).
7. Claim(s) 18-23 and 27-34 is/are rejected under 35 U.S.C. 103 as being unpatentable over Osesina U.S. Patent No. 10,997,134 (herein as ‘Osesina’) and further in view of Lightner et al. U.S. Patent No. 9,619,571 (herein as ‘Lightner’) and Charnock et al. U.S. Patent Application Publication No. 2021/0174128 (herein as ‘Charnock’) and Hansen et al. U.S. Patent No. 9,779,363 (herein as ‘Hansen’).
As to claim 18 Osesina in combination with Lightner and Charnock teaches each and every limitation of claim 17.
Osesina in combination with Lightner and Charnock does not teach but Hansen teaches wherein the memory comprises further instructions that when executed by the processor, further cause the processor to: responsive to determining that the one or more tokens are related to employee data, disambiguate and classify employee attributes from the one or more tokens, wherein the employee attribute comprises an employee skill, an employee job title, a location of employee, a gender, and an educational qualifications (Col. 5 Lines 17-25 Hansen discloses the name associated with education affiliation).
Osesina and Charnock are analogous art because they are in the same field of endeavor, attribute processing. It would have been obvious to one of ordinary skill in the art, before the effective filing date, to modify the identifying of records of Osesina to include creating data structures of Hansen, to allow for retrieval of relevant documents. The suggestion/motivation to combine is that it would be obvious to try in order to gather relevant data quickly (Col. 1 Lines 14-26 Hansen).
As to claim 19 Osesina in combination with Lightner and Charnock teaches each and every limitation of claim 16.
Osesina in combination with Lightner and Charnock does not teach but Hansen teaches wherein the memory comprises further instructions that when executed by the processor, further cause the processor to generate fingerprints corresponding to the entity name (Col. 4 Lines 1-4 Hansen discloses the content item is tracked).
Osesina and Charnock are analogous art because they are in the same field of endeavor, attribute processing. It would have been obvious to one of ordinary skill in the art, before the effective filing date, to modify the identifying of records of Osesina to include creating data structures of Hansen, to allow for retrieval of relevant documents. The suggestion/motivation to combine is that it would be obvious to try in order to gather relevant data quickly (Par. 0017-0018 Hansen).
As to claim 20 Osesina in combination with Lightner and Charnock teaches each and every limitation of claim 16.
Osesina in combination with Lightner and Charnock does not teach but Hansen teaches further cause the processor to query a fingerprints database to find a potential candidate fingerprint matching one or more of the fingerprints corresponding to the entity name, the potential candidate fingerprint and the fingerprints corresponding to the entity name being further compared (Col. 3 Lines 55-60 Hansen discloses the items are associated with the content patterns. Col. 4 Lines 1-4 Hansen discloses the content item is tracked).
Osesina and Charnock are analogous art because they are in the same field of endeavor, attribute processing. It would have been obvious to one of ordinary skill in the art, before the effective filing date, to modify the identifying of records of Osesina to include creating data structures of Hansen, to allow for retrieval of relevant documents. The suggestion/motivation to combine is that it would be obvious to try in order to gather relevant data quickly (Par. 0017-0018 Hansen).
As to claim 21 Osesina in combination with Lightner and Charnock teaches each and every limitation of claim 16.
Osesina in combination with Lightner and Charnock does not teach but Hansen teaches wherein the memory comprises further instructions that when executed by the processor, further cause the processor to perform semantic embedding on the one more tokens to generate a vectorized representation of a semantic meaning of attribute values of the one or more attributes (Col. 6 Lines 5-25 Hansen discloses the items are associated with the feature vectors).
Osesina and Hansen are analogous art because they are in the same field of endeavor, attribute processing. It would have been obvious to one of ordinary skill in the art, before the effective filing date, to modify the identifying of records of Osesina to include the data labeling of Hansen, to allow for retrieval of relevant documents. The suggestion/motivation to combine is that it would be obvious to try in order to identify the correct information (Col. 1 Lines 25-29 Hansen).
As to claim 22 Osesina in combination with Lightner and Charnock teaches each and every limitation of claim 17.
Osesina in combination with Lightner and Charnock does not teach but Hansen teaches wherein the overlapping durations comprise overlapping time periods of validity for the respective timeslice objects (Col. 6 Lines 5-11 Hansen discloses overlap between features).
Osesina and Hansen are analogous art because they are in the same field of endeavor, attribute processing. It would have been obvious to one of ordinary skill in the art, before the effective filing date, to modify the identifying of records of Osesina to include the data labeling of Hansen, to allow for retrieval of relevant documents. The suggestion/motivation to combine is that it would be obvious to try in order to identify the correct information (Col. 1 Lines 25-29 Hansen).
As to claim 23 Osesina in combination with Lightner and Charnock teaches each and every limitation of claim 17.
Osesina in combination with Lightner and Charnock does not teach but Hansen teaches wherein the subset of timeslice objects corresponds to an attribute pair (Col. 3 Lines 63-67 Hansen discloses identifying the pair of fields associated with the values).
Osesina and Hansen are analogous art because they are in the same field of endeavor, attribute processing. It would have been obvious to one of ordinary skill in the art, before the effective filing date, to modify the identifying of records of Osesina to include the data labeling of Hansen, to allow for retrieval of relevant documents. The suggestion/motivation to combine is that it would be obvious to try in order to identify the correct information (Col. 1 Lines 25-29 Hansen).
As to claim 27 Osesina in combination with Lightner and Charnock teaches each and every limitation of claim 26.
In addition Hansen teaches further comprising: responsive to determining that the one or more tokens are related to employee data, disambiguating and classifying employee attributes from the one or more tokens, wherein the employee attribute comprises an employee skill, an employee job title, a location of employee, a gender, and an educational qualifications (Col. 5 Lines 17-25 Hansen discloses the name associated with education affiliation).
Osesina and Hansen are analogous art because they are in the same field of endeavor, attribute processing. It would have been obvious to one of ordinary skill in the art, before the effective filing date, to modify the identifying of records of Osesina to include the data labeling of Hansen, to allow for retrieval of relevant documents. The suggestion/motivation to combine is that it would be obvious to try in order to identify the correct information (Col. 1 Lines 25-29 Hansen).
As to claim 28 Osesina in combination with Lightner and Charnock teaches each and every limitation of claim 25.
Osesina in combination with Lightner and Charnock does not teach but Hansen teaches further comprising generating fingerprints corresponding to the entity name (Col. 4 Lines 1-4 Hansen discloses the content item is tracked).
Osesina and Hansen are analogous art because they are in the same field of endeavor, attribute processing. It would have been obvious to one of ordinary skill in the art, before the effective filing date, to modify the identifying of records of Osesina to include the data labeling of Hansen, to allow for retrieval of relevant documents. The suggestion/motivation to combine is that it would be obvious to try in order to identify the correct information (Col. 1 Lines 25-29 Hansen).
As to claim 29 Osesina in combination with Lightner and Charnock teaches each and every limitation of claim 28.
Osesina in combination with Lightner and Charnock does not teach but Hansen teaches further comprising querying a fingerprints database to find a potential candidate fingerprint matching one or more of the fingerprints corresponding to the entity name, the potential candidate fingerprint and the fingerprints corresponding to the entity name being further compared (Col. 3 Lines 55-60 Hansen discloses the items are associated with the content patterns. Col. 4 Lines 1-4 Hansen discloses the content item is tracked).
Osesina and Hansen are analogous art because they are in the same field of endeavor, attribute processing. It would have been obvious to one of ordinary skill in the art, before the effective filing date, to modify the identifying of records of Osesina to include the data labeling of Hansen, to allow for retrieval of relevant documents. The suggestion/motivation to combine is that it would be obvious to try in order to identify the correct information (Col. 1 Lines 25-29 Hansen).
As to claim 30 Osesina in combination with Lightner and Charnock teaches each and every limitation of claim 25.
Osesina in combination with Lightner and Charnock does not teach but Hansen teaches further comprising performing semantic embedding on the one more tokens to generate a vectorized representation of a semantic meaning of attribute values of the one or more attributes (Col. 6 Lines 5-25 Hansen discloses the items are associated with the feature vectors).
Osesina and Hansen are analogous art because they are in the same field of endeavor, attribute processing. It would have been obvious to one of ordinary skill in the art, before the effective filing date, to modify the identifying of records of Osesina to include the data labeling of Hansen, to allow for retrieval of relevant documents. The suggestion/motivation to combine is that it would be obvious to try in order to identify the correct information (Col. 1 Lines 25-29 Hansen).
As to claim 31 Osesina in combination with Lightner and Charnock teaches each and every limitation of claim 24.
Osesina in combination with Lightner and Charnock does not teach but Hansen teaches wherein the selection of the attribute pair is based on overlapping start and end times associated with the attributes of the attribute pair (Col. 6 Lines 5-11 Hansen discloses overlap between features. Col. 9 lines 25-33 Hansen discloses the time period such as 30 days).
Osesina and Hansen are analogous art because they are in the same field of endeavor, attribute processing. It would have been obvious to one of ordinary skill in the art, before the effective filing date, to modify the identifying of records of Osesina to include the data labeling of Hansen, to allow for retrieval of relevant documents. The suggestion/motivation to combine is that it would be obvious to try in order to identify the correct information (Col. 1 Lines 25-29 Hansen).
As to claim 32 Osesina in combination with Lightner and Charnock teaches each and every limitation of claim 25.
Osesina in combination with Lightner and Charnock does not teach but Hansen wherein the start and end times indicate respective validity periods for the attributes (Col. 6 Lines 5-11 Hansen discloses overlap between features. Col. 9 lines 25-33 Hansen discloses the time period such as 30 days).
Osesina and Hansen are analogous art because they are in the same field of endeavor, attribute processing. It would have been obvious to one of ordinary skill in the art, before the effective filing date, to modify the identifying of records of Osesina to include the data labeling of Hansen, to allow for retrieval of relevant documents. The suggestion/motivation to combine is that it would be obvious to try in order to identify the correct information (Col. 1 Lines 25-29 Hansen).
As to claim 33 Osesina in combination with Lightner and Charnock teaches each and every limitation of claim 25.
Osesina in combination with Lightner and Charnock does not teach but Hansen further comprising arranging the timeslice objects and corresponding indices representative of the start and end times in accordance with a timeslice object timeline (Col. 6 Lines 5-11 Hansen discloses overlap between features. Col. 9 lines 25-33 Hansen discloses the time period such as 30 days. The start is the beginning of 30 days, the end is the end of the 30 days).
Osesina and Hansen are analogous art because they are in the same field of endeavor, attribute processing. It would have been obvious to one of ordinary skill in the art, before the effective filing date, to modify the identifying of records of Osesina to include the data labeling of Hansen, to allow for retrieval of relevant documents. The suggestion/motivation to combine is that it would be obvious to try in order to identify the correct information (Col. 1 Lines 25-29 Hansen).
As to claim 34 Osesina in combination with Lightner and Charnock teaches each and every limitation of claim 33.
Osesina in combination with Lightner and Charnock does not teach but Hansen determining a position of a new timeslice object on the timeslice object timeline based on the new timeslice's respective start and end time (Col. 6 Lines 5-11 Hansen discloses overlap between features. Col. 9 lines 25-33 Hansen discloses the time period such as 30 days. The start is the beginning of 30 days, the end is the end of the 30 days).
Osesina and Hansen are analogous art because they are in the same field of endeavor, attribute processing. It would have been obvious to one of ordinary skill in the art, before the effective filing date, to modify the identifying of records of Osesina to include the data labeling of Hansen, to allow for retrieval of relevant documents. The suggestion/motivation to combine is that it would be obvious to try in order to identify the correct information (Col. 1 Lines 25-29 Hansen).
Conclusion
8. THIS ACTION IS MADE FINAL. 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.
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/J.A.M/ May 29, 2026Examiner, Art Unit 2159
/ANN J LO/Supervisory Patent Examiner, Art Unit 2159
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