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 .
This Office Action is responsive to communication filed on 04/22/2025.
Claims 1 – 20 are currently pending.
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 – 20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1 - 20 of U.S. Patent No. 12,321,355 B2. Although the claims at issue are not identical, they are not patentably distinct from each other because subject matter claim in the instant application can also found in patent ‘355.
Certain limitation found in claim 1 of ‘355 but not in instant application such as “causing to display, at a graphical user interface associated with a genealogy online system, a search box, the genealogy online system configured to provide functions comprising family-tree building and historical record search…the machine learning language model being trained to receive a query and classify the query to an intent mappable to a plurality of functions of the genealogy online system, wherein the machine learning language model is a transformer model”.
It would have been obvious to one with ordinary skill in the art before the effective filling date of the claim invention to broaden the claim at no additional cost in development.
The following is the comparison between claim 1 of instant application and patent ‘355.
Instant application ‘682 Patent ‘355
A computer-implemented method comprising:
A computer-implemented method for linking a natural- language user query at a genealogy online system to a specific preexisting function of the genealogy online system, the computer-implemented method comprising:
causing to display, at a graphical user interface associated with a genealogy online system, a search box, the genealogy online system configured to provide functions comprising family-tree building and historical record search;
receiving a natural language query at a genealogy online system communicating with a large language model, the genealogy online system comprising a function architecture supporting a plurality of genealogy online system functions;
receiving a query from a user entered at the search box;
extracting, from the natural language query, an intent by processing the natural language query utilizing the large language model;
using a machine learning language model to determine an intent of the user associated with the query, the machine learning language model being trained to receive a query and classify the query to an intent mappable to a plurality of functions of the genealogy online system, wherein the machine learning language model is a transformer model;
mapping the determined intent from the machine learning language model to a plurality of functions of a predetermined table of intents and associated functions of the genealogy online system;
determining a genealogy online system function corresponding to the intent from among the plurality of genealogy online system functions supported by the function architecture;
outputting a prediction regarding the mapped plurality of functions of the genealogy online system based on the mapping of the determined intent of the user;
and generating a response for the genealogy online system function utilizing, from the function architecture, a function engine corresponding to the genealogy online system function.
and causing to display, at the graphical user interface as a result of the query, one or more links to the predicted one or more functions of the genealogy online system based on the intent determined by the machine learning language model.
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 – 20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1:
Claims 1 - 20 are directed to a "method, system, and a non-transitory computer readable medium", and therefore, directed to a statutory category.
Step 2A, Prong One:
The independent claims 1, 8, 15 includes the following limitations that directed to an abstract idea:
“extracting, from the natural language query, an intent by processing the natural language query utilizing the large language model”, as drafted, recites a mentally process as an evaluation or judgement. A user can mentally judge/evaluation the query and identify the intent of the query. This is also consistent with the specification as in Para. 0037 of the Disclosure, where one can mentally perform parsing the search query and identifying intents. See Federal Circuit case law (such as Dialect, LLC v. Amazon) establishes that "understanding language using context" or "comprehending meaning and indicating results" falls into the Mental Processes category of abstract ideas.
“determining a genealogy online system function corresponding to the intent from among the plurality of genealogy online system functions supported by the function architecture” as drafted, recites a mentally process as an evaluation or judgement. A user can mentally judge/evaluation intent and matching with corresponding known function. This is also consistent with the specification as in Para. 0032 of the Disclosure, where the extracted intent was matched with existing function or activity.
Step 2A, Prong Two:
The claim recites the following additional elements:
“receiving a natural language query at a genealogy online system communicating with a large language model, the genealogy online system comprising a function architecture supporting a plurality of genealogy online system functions” which are insignificant extra solution activities as retrieval/receiving of data (i.e. mere data gathering) such as obtain information (input a natural language query) for "extracting” and “determining the intent”, as identified in MPEP 2106.05(g) and does not provide integration into a practical application.
“generating a response for the genealogy online system function utilizing, from the function architecture, a function engine corresponding to the genealogy online system function”, as drafted, recites a mentally process as an evaluation or judgement. Receiving information, analyzing it, and generating a response is fundamentally a mental process, even when done on a computer. Generating, processing, and outputting data (like genealogy records or responses) using standard computer architecture falls under abstract data manipulation.
The system includes one or more processor, memory having instruction, which is a high-level recitation of a generic computer components and represents mere instructions to apply on a computer as in MPEP 2106.05(f), which does not provide integration into a practical application.
The additional limitations, individually or in combination, do not integrated the abstract idea into a practical application, even viewing the claims as a whole, because it does not impose any meaningful limits on practicing the abstract idea.
Step 2B
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception.
In this case, the "receiving … generating response…" are identified as insignificant extra-solution activity above when re-evaluated these elements are well-understood, routine, and conventional as evidenced by the court cases in MPEP 2106.05(d)(II),' "i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); "computer-implemented", and performed by "one or more processors", a system includes memory storing instruction coupled to a processor, are considered insignificant extra- solution activity, and do not take the claim limitations out of the mental processes grouping. See MPEP - 2106.05(g) ("whether the limitation is significant").
Accordingly, the additional limitations are not providing significantly more than the
judicial exception. Looking at the claim as a whole does not change this conclusion and
therefore, the claim is ineligible.
The dependent claims 2 includes “wherein extracting the intent comprises utilizing the large language model trained according to the plurality of genealogy online system functions supported by the function architecture”, as drafted this recites a mentally performable process as an evaluation or judgement. Merely instructing a computer to "extract intent utilizing an LLM" or applying it broadly to a specific business field (such as "genealogy online systems") is insufficient. Under its broadest reasonable interpretation when read in light of the specification, this limitation is recited at a high level of generality, can be performed by human mind, which is a form of metal activity. See MPEP 2106.04(a)(2), subsection III.
The dependent claims 3 includes “wherein extracting the intent from the natural language query comprises utilizing the large language model to process text of the natural language query together with text of past queries corresponding to the natural language query” as drafted this recites a mentally performable process as an evaluation or judgement. Merely instructing a computer to "extract intent utilizing an LLM" or applying it broadly to a specific business field (such as "genealogy online systems") is insufficient. Under its broadest reasonable interpretation when read in light of the specification, this limitation is recited at a high level of generality, can be performed by human mind, which is a form of metal activity. See MPEP 2106.04(a)(2), subsection III.
The dependent claims 4 - 5 includes “wherein the function architecture comprises a plurality of function engines that support respective genealogy online system functions from among the plurality of genealogy online system functions by accessing databases and executing processes specific to the respective genealogy online system functions”, which are insignificant extra solution activities as they are known computer functions. Merely automating known mental processes or business practices (like keeping genealogical records) on a computer does not make it patentable. Using generic "function engines" and "databases" to execute processes is considered routine, conventional computer activity.
The dependent claims 6 includes “wherein determining the genealogy online system function corresponding to the intent comprises utilizing the large language model to predict an intent category corresponding to the natural language query from among a predefined set of intent categories supported by the genealogy online system”, as drafted, recites a mentally process as an evaluation or judgement. Merely automating known mental processes or business practices (like keeping genealogical records) on a computer does not make it patentable. Using generic "function engines" and "databases" to execute processes is considered routine, conventional computer activity.
The dependent claims 7 includes “wherein generating the response comprises automatically executing the genealogy online system function utilizing the function engine”, as drafted, recites a mentally process as an evaluation or judgement. Merely automating known mental processes or business practices (like keeping genealogical records) on a computer does not make it patentable. Using generic "function engines" and "databases" to execute processes is considered routine, conventional computer activity
Claims 8 - 20, Applicant claims the abstract idea on a system, a non-transitory computer readable medium, with processors and instructions to carry-out the method as in claim 1, without adding further limitations that amount to more than generally linking the use of the exception to a particular technological environment. Generic computer components recited as performing generic computer functions that are well-understood, routine and conventional activities amount to no more than implementing the abstract idea with a computerized system. The use of generic computer components to “receiving …extracting… determining… and generating response" do not impose any meaningful limit on the computer implementation of the abstract idea. Thus, taken alone, the additional elements do not amount to significantly more than the above-identified judicial exception (the abstract idea).
Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation. The claims are not patent eligible.
Claim Rejections - 35 USC § 103
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.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 1 - 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Yang et al (U.S. 2020/0250197 A1) in view of Marks et al (U.S. 2024/0046142 A1).
♦ As per claims 1, 8, 15,
Yang discloses a computer-implemented method, system (Fig. 1, 6) comprising:
- “receiving a natural language query at a genealogy online system communicating with a large language model, the genealogy online system comprising a function architecture supporting a plurality of genealogy online system functions” See Fig. 2, Para. 0014, 0016, 0027, 0030 of Yang wherein databases may include “Although some of the description relates to searching for genealogical records from genealogical databases, the search system can more generally search for various other types of records on other types of databases”, and “The client device 110 receives user queries via the user interface 115 … The client device 110 includes a user interface 115 configured to receive user queries from a user of the client device 110. The user interface 115 may include both input devices and output devices. … In one embodiment, the user interface 115 includes a graphical user interface (GUI) that includes one or more search fields to accept user queries from the end user and that displays searched and ranked results that are provided by the search system 120. … In some embodiments, the user interface 115 may also include an application programming interface (API)… user queries may be formatted to include multiple character strings provided via the one or more search fields”.
- “extracting, from the natural language query, an intent by processing the natural language query utilizing the large language model” See Para. 0018, 0021, 0027 of Yang wherein characteristics from the query are identified, (“The query processing module 140 processes a user query to generate an enhanced query including one or more expanded characteristics. The query processing module 140 identifies specified characteristics in the user query”, “The machine learning model may be trained with a training dataset that includes a plurality of historical search results that pair user query with the historical user actions and search results”, “The user query 205 may specify one or more genealogical characteristics. The search system 120 processes the user query 205 to determine an enhanced query 210. The enhanced query 210 may include the specified characteristics in addition to expanded characteristics, e.g., via the fuzzy operation”).
- “determining a genealogy online system function corresponding to the intent from among the plurality of genealogy online system functions supported by the function architecture” See Para. 0018, 0021 of Yang wherein different characteristic (intent) corresponds to a particular database, (“Tailoring the enhanced query may include filtering out various specified and/or expanded characteristics of less relevance to a particular database”, “the machine learning model is trained to determine the relevancy of records from a particular database based on the characteristics”).
- “generating a response for the genealogy online system function utilizing, from the function architecture, a function engine corresponding to the genealogy online system function” See Para. 0019 of Yang wherein database returns the search results, (“the record retrieval module 150 searches for and retrieves records using the specified characteristics and/or the expanded characteristics…Each database may return a search result that includes a plurality of records”).
In case that the Applicant disagrees, Yang teaches “using the machine learning model to determine an intent of the user”, the Examiner provides another example.
Marks, in the same field of endeavor, discloses a method, system that discovers automatable tasks and/or determines task variants in data (See abstract of Marks). In particular, Marks teaches:
*“using a machine learning language model to determine an intent of the user associated with the query” See abstract, Para. 0161 – 163, Fig. 11 of Marks wherein “Semantic understanding of user actions by artificial intelligence (AI)/machine learning (ML) model(s), for example, may be applied to determine the intent of the user rather than only focusing on what actions the user is performing on the computing system”, “This information is then used to train a clustering AI/ML model at 1110 to cluster information from screens into a trace of a sequence of clusters for the screens. A classifier AI/ML model is then trained to classify the traces of sequences of clusters into task types at 1115”.
It would have been obvious to one with ordinary skill in the art before the effective filling date of the claim invention apply the teaching of Marks into the invention of Yang since both inventions were available and the combination would provide more accurate determination of what the user actually intends to do and therefore reduce the time searching for information.
♦ As per claims 2, 9, 16,
- “wherein extracting the intent comprises utilizing the large language model trained according to the plurality of genealogy online system functions supported by the function architecture” See Para. 0161 – 163, Fig. 11 of Marks wherein “A classifier AI/ML model is then trained to classify the traces of sequences of clusters (data from query) into task types at 1115. In some embodiments, the classifier AI/ML model is configured to compare the sequence of clusters in the trace from the clustering AI/ML model to other sequences of clusters representing traces from previously identified task types to determine the task type”, “The classifier AI/ML model is then run on the sequence of clusters in the trace from the clustering AI/ML model, taking the sequence of clusters in the trace as input and providing a task type (if identified) as an output. …, the classified task type is mapped to an RPA workflow that accomplishes an intent of the captured task flow at 1130. In some embodiments, the mapping includes using system information, semantic information from an NLP model, or both, to provide context to the classified task type”.
♦ As per claims 3, 10, 17,
- “wherein extracting the intent from the natural language query comprises utilizing the large language model to process text of the natural language query together with text of past queries corresponding to the natural language query.” See Para. 0030 of Yang for historical query. See Para. 0161 – 163, Fig. 11 of Marks wherein “A classifier AI/ML model is then trained to classify the traces of sequences of clusters (data from query) into task types at 1115. In some embodiments, the classifier AI/ML model is configured to compare the sequence of clusters in the trace from the clustering AI/ML model to other sequences of clusters representing traces from previously identified task types to determine the task type”, “The classifier AI/ML model is then run on the sequence of clusters in the trace from the clustering AI/ML model, taking the sequence of clusters in the trace as input and providing a task type (if identified) as an output. …, the classified task type is mapped to an RPA workflow that accomplishes an intent of the captured task flow at 1130. In some embodiments, the mapping includes using system information, semantic information from an NLP model, or both, to provide context to the classified task type”.
♦ As per claims 4 - 5, 11 - 12,18 – 19,
“wherein the function architecture comprises a plurality of function engines that support respective genealogy online system functions from among the plurality of genealogy online system functions by accessing databases and executing processes specific to the respective genealogy online system functions” See Para. 0018, 0021 of Yang wherein different characteristic (intent) corresponds to a particular database, (“Tailoring the enhanced query may include filtering out various specified and/or expanded characteristics of less relevance to a particular database”, “the machine learning model is trained to determine the relevancy of records from a particular database based on the characteristics”).
♦ As per claims 6, 13, 20
- “wherein determining the genealogy online system function corresponding to the intent comprises utilizing the large language model to predict an intent category corresponding to the natural language query from among a predefined set of intent categories supported by the genealogy online system” See Para. 0018, 0021 of Yang wherein different characteristic (intent) corresponds to a particular database, (“Tailoring the enhanced query may include filtering out various specified and/or expanded characteristics of less relevance to a particular database”, “the machine learning model is trained to determine the relevancy of records from a particular database based on the characteristics”).
♦ As per claim 7, 14,
- “wherein generating the response comprises automatically executing the genealogy online system function utilizing the function engine” See Para. 0019 of Yang wherein database returns the search results, (“the record retrieval module 150 searches for and retrieves records using the specified characteristics and/or the expanded characteristics…Each database may return a search result that includes a plurality of records”).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CAM LINH T NGUYEN whose telephone number is (571)272-4024 or camlinh.nguyen@uspto.gov . The examiner can normally be reached M-F: 7:00 - 3:00 pm.
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/CAM LINH T NGUYEN/Primary Examiner, Art Unit 2161
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