DETAILED ACTION
This Office action is in response to original application filed on 03/27/2025.
Claims 1-20 are pending. Claims 1-20 are rejected.
Notice of 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 .
Statutory Review under 35 USC § 101
Claims 1-7 are directed towards a method and have been reviewed.
Claims 1-7 appear to be directed to an abstract idea without significantly more and thus are patent-ineligible based on the subject matter eligibility consideration.
Claims 8-14 are directed toward an article of manufacture and have been reviewed.
Claims 8-14 initially appear to be statutory, as the article of manufacture excludes transitory signals (claim says non-transitory).
However, claims 8-14 appear to be directed to an abstract idea without significantly more and thus are patent-ineligible based on the subject matter eligibility consideration.
Claims 15-20 are directed toward a system and have been reviewed.
Claims 15-20 initially appear to be statutory as the system contains hardware.
However, claims 15-20 appear to be directed to an abstract idea without significantly more and thus are patent-ineligible based on the subject matter eligibility consideration.
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.
(I)
Claims 1-7 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claim 1 recites identifying at least one evidence passage and analyzing the at least one evidence passage, which is a mental process (including an observation, evaluation, judgment, opinion).
Step 2A, Prong Two
This judicial exception of identifying at least one evidence passage and analyzing the at least one evidence passage is not integrated into a practical application despite the generically recited computer elements shown below:
a graphical user interface (GUI)
a user device,
The generically recited computer elements amount to implementing the abstract idea on a computer, merely using a computer as a tool to perform an abstract idea, or generally linking the use of a judicial exception to a particular technological environment or field of use as seen below.
a graphical user interface (GUI) presented via a user device,
generating a query result indicating the at least one evidence passage that represents the connection between the first concept and the second concept; and
visually displaying, via the GUI presented via the user device, the query result.
These additional elements are mere generic transmission and presentation of collected and analyzed data which is considered to be insignificant extra solution activity (MPEP 2106.05(g)).
performing, based at least in part on the input query, a search of a plurality of knowledge data sources that each include a plurality of documents;
These additional elements are mere data gathering which is considered to be insignificant extra solution activity (MPEP 2106.05(g)).
Step 2B
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception despite the additional elements shown below:
receiving, via a graphical user interface (GUI) presented via a user device, an input query that is associated with a research topic and that includes a first concept and a second concept,
This performs receiving or transmitting data over a network, which are well-understood, routine, conventional computer functions as recognized by the court decisions listed in MPEP § 2106.05(d), specifically MPEP § 2106.05(d)(II)(i).
performing, based at least in part on the input query, a search of a plurality of knowledge data sources that each include a plurality of documents;
generating a query result indicating the at least one evidence passage that represents the connection between the first concept and the second concept; and
visually displaying, via the GUI presented via the user device, the query result.
These additional elements perform gathering and analyzing information using conventional techniques and displaying the result, which is considered to not be sufficient to show improvement to the functioning of a computer or to any other technology or technical field (MPEP 2106.05(a)).
Claims 2-4 do not add meaningful limitations as these are merely nominal or token extra-solution components of the claim and serves only as an attempt to generally link the product of nature to a further particular technological environment (see MPEP 2106.05(h)).
Claim 5 comprises determining a first score, identifying at least one second evidence passage, and analyzing the at least one second evidence passage, additional steps of a mental process/abstract idea.
Claim 6 further comprises a determining by aggregating based at least in part on a degree of semantic similarity, another step of a mental process/abstract idea.
Claim 7 further comprises a determining of an aggregation confidence based at least in part on a reliability score, which is another step of an abstract idea.
(II)
Claims 8-14 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claim 8 recites identifying at least one evidence passage and analyzing the at least one evidence passage, which is a mental process (including an observation, evaluation, judgment, opinion).
Step 2A, Prong Two
This judicial exception of identifying at least one evidence passage and analyzing the at least one evidence passage is not integrated into a practical application despite the generically recited computer elements shown below:
one or more non-transitory computer-readable media
one or more processors,
a graphical user interface (GUI)
a user device,
The generically recited computer elements amount to implementing the abstract idea on a computer, merely using a computer as a tool to perform an abstract idea, or generally linking the use of a judicial exception to a particular technological environment or field of use as seen below.
cause the one or more processors to perform operations comprising:
This additional element merely uses a computer as a tool to perform an abstract idea (see MPEP 2160.05(f)).
a graphical user interface (GUI) presented via a user device,
generating a query result indicating the at least one evidence passage that represents the connection between the first concept and the second concept; and
visually displaying, via the GUI presented via the user device, the query result.
These additional elements are mere generic transmission and presentation of collected and analyzed data which is considered to be insignificant extra solution activity (MPEP 2106.05(g)).
performing, based at least in part on the input query, a search of a plurality of knowledge data sources that each include a plurality of documents;
These additional elements are mere data gathering which is considered to be insignificant extra solution activity (MPEP 2106.05(g)).
Step 2B
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception despite the additional elements shown below:
One or more non-transitory computer-readable media storing one or more computer-executable instructions
These elements store and retrieve information in memory, which are well-understood, routine, conventional computer functions as recognized by the court decisions listed in MPEP § 2106.05(d).
receiving, via a graphical user interface (GUI) presented via a user device, an input query that is associated with a research topic and that includes a first concept and a second concept,
This performs receiving or transmitting data over a network, which are well-understood, routine, conventional computer functions as recognized by the court decisions listed in MPEP § 2106.05(d), specifically MPEP § 2106.05(d)(II)(i).
performing, based at least in part on the input query, a search of a plurality of knowledge data sources that each include a plurality of documents;
generating a query result indicating the at least one evidence passage that represents the connection between the first concept and the second concept; and
visually displaying, via the GUI presented via the user device, the query result.
These additional elements perform gathering and analyzing information using conventional techniques and displaying the result, which is considered to not be sufficient to show improvement to the functioning of a computer or to any other technology or technical field (MPEP 2106.05(a)).
Claims 9-11 do not add meaningful limitations as these are merely nominal or token extra-solution components of the claim and serves only as an attempt to generally link the product of nature to a further particular technological environment (see MPEP 2106.05(h)).
Claim 12 comprises determining a first score, identifying at least one second evidence passage, and analyzing the at least one second evidence passage, additional steps of a mental process/abstract idea.
Claim 13 further comprises a determining by aggregating based at least in part on a degree of semantic similarity, another step of a mental process/abstract idea.
Claim 14 further comprises a determining of an aggregation confidence based at least in part on a reliability score, which is another step of an abstract idea.
(III)
Claims 15-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claim 15 recites identifying at least one evidence passage and analyzing the at least one evidence passage, which is a mental process (including an observation, evaluation, judgment, opinion).
Step 2A, Prong Two
This judicial exception of identifying at least one evidence passage and analyzing the at least one evidence passage is not integrated into a practical application despite the generically recited computer elements shown below:
memory;
one or more processors;
a graphical user interface (GUI)
a user device,
The generically recited computer elements amount to implementing the abstract idea on a computer, merely using a computer as a tool to perform an abstract idea, or generally linking the use of a judicial exception to a particular technological environment or field of use as seen below.
executable by the one or more processors to perform operations comprising:
This additional element merely uses a computer as a tool to perform an abstract idea (see MPEP 2160.05(f)).
a graphical user interface (GUI) presented via a user device,
generating a query result indicating the at least one evidence passage that represents the connection between the first concept and the second concept; and
visually displaying, via the GUI presented via the user device, the query result.
These additional elements are mere generic transmission and presentation of collected and analyzed data which is considered to be insignificant extra solution activity (MPEP 2106.05(g)).
performing, based at least in part on the input query, a search of a plurality of knowledge data sources that each include a plurality of documents;
These additional elements are mere data gathering which is considered to be insignificant extra solution activity (MPEP 2106.05(g)).
Step 2B
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception despite the additional elements shown below:
one or more computer-executable instructions stored in the memory
These elements store and retrieve information in memory, which are well-understood, routine, conventional computer functions as recognized by the court decisions listed in MPEP § 2106.05(d).
receiving, via a graphical user interface (GUI) presented via a user device, an input query that is associated with a research topic and that includes a first concept and a second concept,
This performs receiving or transmitting data over a network, which are well-understood, routine, conventional computer functions as recognized by the court decisions listed in MPEP § 2106.05(d), specifically MPEP § 2106.05(d)(II)(i).
performing, based at least in part on the input query, a search of a plurality of knowledge data sources that each include a plurality of documents;
generating a query result indicating the at least one evidence passage that represents the connection between the first concept and the second concept; and
visually displaying, via the GUI presented via the user device, the query result.
These additional elements perform gathering and analyzing information using conventional techniques and displaying the result, which is considered to not be sufficient to show improvement to the functioning of a computer or to any other technology or technical field (MPEP 2106.05(a)).
Claims 16-18 do not add meaningful limitations as these are merely nominal or token extra-solution components of the claim and serves only as an attempt to generally link the product of nature to a further particular technological environment (see MPEP 2106.05(h)).
Claim 19 comprises determining a first score, identifying at least one second evidence passage, and analyzing the at least one second evidence passage, additional steps of a mental process/abstract idea.
Claim 20 further comprises a determining by aggregating based at least in part on a degree of semantic similarity and determining of an aggregation confidence based at least in part on a reliability score, which are additional steps of an abstract idea.
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.
Claims 1-2, 4-6; 8-9, 11-13; 15-16, and 18-19 are rejected under 35 U.S.C. 103 as being unpatentable over Tripathi et al., U.S. Patent Application Publication No. 2019/0005124 (hereinafter Tripathi) in view of Stubley et al., U.S. Patent Application Publication No. 2016/0179934 (hereinafter Stubley).
Regarding claim 1, Tripathi teaches:
A method comprising: receiving, via a graphical user interface (GUI) presented via a user device, an input query that is associated with a research topic and that includes a first concept and a second concept, the research topic being associated with an inquiry regarding whether a relationship exists between the first concept and the second concept; (Tripathi FIG. 1, FIG. 5, ¶ 0124: At a step 502, a first input area, for receiving the search query from the user, is provided on a first user-interface of the computing device. At a step 504, one or more query segments and relations between the one or more query segments are displayed on a second area of the first user-interface. The received search query is developed to obtain the one or more query segments and the relations between the one or more query segments ... a list of one or more concepts [relevant to research topic] associated with the extracted search results)
performing, based at least in part on the input query, a search of a plurality of knowledge data sources that each include a plurality of documents; (Tripathi FIG. 1, FIG. 5, ¶ 0124: At a step 506, an arranged set of extracted search results is provided in a third area of the first user-interface. The search results are extracted, from at least one database [shows a plurality of knowledge data sources], based on the developed search query and arranged based on one or more parameters associated with the extracted search results ... the information related to the selected search result comprises a summary of the selected search result, one or more documents associated with the selected search result [shows plurality of documents])
…
generating a query result … that represents the connection between the first concept and the second concept; and (Tripathi FIG. 1, FIG. 5, ¶ 0124: The received search query is developed to obtain the one or more query segments and the relations between the one or more query segments [shows connection between concepts]. At a step 506, an arranged set of extracted search results is provided in a third area of the first user-interface. The search results are extracted, from at least one database, based on the developed search query [shows generating])
visually displaying, via the GUI presented via the user device, the query result. (Tripathi FIG. 1, FIG. 5, ¶ 0124: At step 510, information related to a selected search result or a selected concept, is provided on a second user-interface, in response to a selection input, from the user, based on one of a search result or a concept associated with the search results. Moreover, the information related to the selected search result comprises a summary of the selected search result, one or more documents associated with the selected search result, and concepts associated with the selected search result. Furthermore, the information related to the selected concept comprises a summary of the selected concept, and one or more documents associated with the selected concept)
Tripathi does not expressly disclose:
identifying, based at least in part on the search, at least one evidence passage that serves as at least one potential link between the first concept and the second concept;
analyzing, using natural language processing, the at least one evidence passage to determine that information included within the at least one evidence passage represents a connection between the first concept and the second concept;
Tripathi further does not expressly disclose generating a query result indicating the at least one evidence passage.
However, Stubley addresses this by teaching:
identifying, based at least in part on the search, at least one evidence passage that serves as at least one potential link between the first concept and the second concept; (Stubley ¶ 0078-0081: the result of applying one or more search queries constructed by query builder 170 to unstructured data set(s) 140 may be a set of documents and/or passages identified as relevant to a search query and passed to evidence scorer 180. The set of returned documents/passages may be thresholded for relevance in any suitable way ... evaluate the retrieved passages in terms of the strength of supporting evidence that they provide for the extracted answer information as contributing to the best answer to the user's question)
analyzing, using natural language processing, the at least one evidence passage to determine that information included within the at least one evidence passage represents a connection between the first concept and the second concept; (Stubley FIG. 5, ¶ 0124: At act 530, documents containing natural language text may be analyzed, including analyzing one or more passages of text in the documents to determine whether the passage entails any of the hypotheses from the question. Exemplary techniques for entailment analysis are described above. At act 540, in response to determining that a passage entails a question hypothesis, the passage may be identified as providing supporting evidence for the generated answer to the question; Stubley ¶ 0084-0086: the strength of a passage's supporting evidence for answer information for a question portion may be evaluated by determining whether the passage entails a hypothesis corresponding to the question portion ... evidence scorer 180 may score passages based at least in part on the degree to which they entail one or more question hypotheses, and may rank passages based on their scores ... an entailment/contradiction score computed as described above ... may be used as one feature input to a statistical classifier used to score the strength of a passage's supporting evidence for an answer item)
Stubley further teaches generating a query result indicating the at least one evidence passage. (Stubley FIG. 5, ¶ 0123-0124: At act 550, the answer and the passage(s) identified as providing supporting evidence for that answer may be presented to the user in response to the input question. In some embodiments, as discussed above, multiple different passages may be scored based at least in part on the strength of the passages' supporting evidence for the answer to the question, and one or more of the passages may be selected for presentation to the user based on the passages' scores)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the functioning of the evidence passage retrieval of Tripathi with the evidence passage retrieval of Stubley.
In addition, both of the references (Tripathi and Stubley) disclose features that are directed to analogous art, and they are directed to the same field of endeavor, such as question answering interfaces.
Motivation to do so would be to improve the functioning of Tripathi returning search result documents in response to compound queries with the functioning in similar reference Stubley also returning search result documents in response to compound queries but with the improvement of scoring techniques.
Motivation to do so would also be the teaching, suggestion, or motivation for a person of ordinary skill in the art to implement designing a QA system to make intelligent use of both structured and unstructured data sources in its knowledge base as seen in Stubley ¶ 0028.
Regarding claim 8, Tripathi teaches:
One or more non-transitory computer-readable media storing one or more computer-executable instructions that, when executed by one or more processors, cause the one or more processors to perform operations comprising: (Tripathi ¶ 0002: the present disclosure also relates to computer readable medium containing program instructions for execution on a computer system, which when executed by a computer, cause the computer to perform method steps for presenting information related to search; Tripathi ¶ 0092: Examples of computing device include, but are not limited to, cellular phones, personal digital assistants (PDAs), handheld devices, wireless modems, laptop computers, personal computers, etc. Additionally, the computing device includes a casing, a memory, a processor)
receiving, via a graphical user interface (GUI) presented via a user device, an input query that is associated with a research topic and that includes a first concept and a second concept, the research topic being associated with an inquiry regarding whether a relationship exists between the first concept and the second concept; (Tripathi FIG. 1, FIG. 5, ¶ 0124: At a step 502, a first input area, for receiving the search query from the user, is provided on a first user-interface of the computing device. At a step 504, one or more query segments and relations between the one or more query segments are displayed on a second area of the first user-interface. The received search query is developed to obtain the one or more query segments and the relations between the one or more query segments ... a list of one or more concepts [relevant to research topic] associated with the extracted search results)
performing, based at least in part on the input query, a search of a plurality of knowledge data sources that each include a plurality of documents; (Tripathi FIG. 1, FIG. 5, ¶ 0124: At a step 506, an arranged set of extracted search results is provided in a third area of the first user-interface. The search results are extracted, from at least one database [shows a plurality of knowledge data sources], based on the developed search query and arranged based on one or more parameters associated with the extracted search results ... the information related to the selected search result comprises a summary of the selected search result, one or more documents associated with the selected search result [shows plurality of documents])
…
generating a query result … that represents the connection between the first concept and the second concept; and (Tripathi FIG. 1, FIG. 5, ¶ 0124: The received search query is developed to obtain the one or more query segments and the relations between the one or more query segments [shows connection between concepts]. At a step 506, an arranged set of extracted search results is provided in a third area of the first user-interface. The search results are extracted, from at least one database, based on the developed search query [shows generating])
visually displaying, via the GUI presented via the user device, the query result. (Tripathi FIG. 1, FIG. 5, ¶ 0124: At step 510, information related to a selected search result or a selected concept, is provided on a second user-interface, in response to a selection input, from the user, based on one of a search result or a concept associated with the search results. Moreover, the information related to the selected search result comprises a summary of the selected search result, one or more documents associated with the selected search result, and concepts associated with the selected search result. Furthermore, the information related to the selected concept comprises a summary of the selected concept, and one or more documents associated with the selected concept)
Tripathi does not expressly disclose:
identifying, based at least in part on the search, at least one evidence passage that serves as at least one potential link between the first concept and the second concept;
analyzing, using natural language processing, the at least one evidence passage to determine that information included within the at least one evidence passage represents a connection between the first concept and the second concept;
Tripathi further does not expressly disclose generating a query result indicating the at least one evidence passage.
However, Stubley addresses this by teaching:
identifying, based at least in part on the search, at least one evidence passage that serves as at least one potential link between the first concept and the second concept; (Stubley ¶ 0078-0081: the result of applying one or more search queries constructed by query builder 170 to unstructured data set(s) 140 may be a set of documents and/or passages identified as relevant to a search query and passed to evidence scorer 180. The set of returned documents/passages may be thresholded for relevance in any suitable way ... evaluate the retrieved passages in terms of the strength of supporting evidence that they provide for the extracted answer information as contributing to the best answer to the user's question)
analyzing, using natural language processing, the at least one evidence passage to determine that information included within the at least one evidence passage represents a connection between the first concept and the second concept; (Stubley FIG. 5, ¶ 0124: At act 530, documents containing natural language text may be analyzed, including analyzing one or more passages of text in the documents to determine whether the passage entails any of the hypotheses from the question. Exemplary techniques for entailment analysis are described above. At act 540, in response to determining that a passage entails a question hypothesis, the passage may be identified as providing supporting evidence for the generated answer to the question; Stubley ¶ 0084-0086: the strength of a passage's supporting evidence for answer information for a question portion may be evaluated by determining whether the passage entails a hypothesis corresponding to the question portion ... evidence scorer 180 may score passages based at least in part on the degree to which they entail one or more question hypotheses, and may rank passages based on their scores ... an entailment/contradiction score computed as described above ... may be used as one feature input to a statistical classifier used to score the strength of a passage's supporting evidence for an answer item)
Stubley further teaches generating a query result indicating the at least one evidence passage. (Stubley FIG. 5, ¶ 0123-0124: At act 550, the answer and the passage(s) identified as providing supporting evidence for that answer may be presented to the user in response to the input question. In some embodiments, as discussed above, multiple different passages may be scored based at least in part on the strength of the passages' supporting evidence for the answer to the question, and one or more of the passages may be selected for presentation to the user based on the passages' scores)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the functioning of the evidence passage retrieval of Tripathi with the evidence passage retrieval of Stubley.
In addition, both of the references (Tripathi and Stubley) disclose features that are directed to analogous art, and they are directed to the same field of endeavor, such as question answering interfaces.
Motivation to do so would be to improve the functioning of Tripathi returning search result documents in response to compound queries with the functioning in similar reference Stubley also returning search result documents in response to compound queries but with the improvement of scoring techniques.
Motivation to do so would also be the teaching, suggestion, or motivation for a person of ordinary skill in the art to implement designing a QA system to make intelligent use of both structured and unstructured data sources in its knowledge base as seen in Stubley ¶ 0028.
Regarding claim 15, Tripathi teaches:
A system comprising: memory; one or more processors; and one or more computer-executable instructions stored in the memory and executable by the one or more processors to perform operations comprising: (Tripathi ¶ 0002: the present disclosure also relates to computer readable medium containing program instructions for execution on a computer system, which when executed by a computer, cause the computer to perform method steps for presenting information related to search; Tripathi ¶ 0092: Examples of computing device include, but are not limited to, cellular phones, personal digital assistants (PDAs), handheld devices, wireless modems, laptop computers, personal computers, etc. Additionally, the computing device includes a casing, a memory, a processor)
receiving, via a graphical user interface (GUI) presented via a user device, an input query that is associated with a research topic and that includes a first concept and a second concept, the research topic being associated with an inquiry regarding whether a relationship exists between the first concept and the second concept; (Tripathi FIG. 1, FIG. 5, ¶ 0124: At a step 502, a first input area, for receiving the search query from the user, is provided on a first user-interface of the computing device. At a step 504, one or more query segments and relations between the one or more query segments are displayed on a second area of the first user-interface. The received search query is developed to obtain the one or more query segments and the relations between the one or more query segments ... a list of one or more concepts [relevant to research topic] associated with the extracted search results)
performing, based at least in part on the input query, a search of a plurality of knowledge data sources that each include a plurality of documents; (Tripathi FIG. 1, FIG. 5, ¶ 0124: At a step 506, an arranged set of extracted search results is provided in a third area of the first user-interface. The search results are extracted, from at least one database [shows a plurality of knowledge data sources], based on the developed search query and arranged based on one or more parameters associated with the extracted search results ... the information related to the selected search result comprises a summary of the selected search result, one or more documents associated with the selected search result [shows plurality of documents])
…
generating a query result … that represents the connection between the first concept and the second concept; and (Tripathi FIG. 1, FIG. 5, ¶ 0124: The received search query is developed to obtain the one or more query segments and the relations between the one or more query segments [shows connection between concepts]. At a step 506, an arranged set of extracted search results is provided in a third area of the first user-interface. The search results are extracted, from at least one database, based on the developed search query [shows generating])
visually displaying, via the GUI presented via the user device, the query result. (Tripathi FIG. 1, FIG. 5, ¶ 0124: At step 510, information related to a selected search result or a selected concept, is provided on a second user-interface, in response to a selection input, from the user, based on one of a search result or a concept associated with the search results. Moreover, the information related to the selected search result comprises a summary of the selected search result, one or more documents associated with the selected search result, and concepts associated with the selected search result. Furthermore, the information related to the selected concept comprises a summary of the selected concept, and one or more documents associated with the selected concept)
Tripathi does not expressly disclose:
identifying, based at least in part on the search, at least one evidence passage that serves as at least one potential link between the first concept and the second concept;
analyzing, using natural language processing, the at least one evidence passage to determine that information included within the at least one evidence passage represents a connection between the first concept and the second concept;
Tripathi further does not expressly disclose generating a query result indicating the at least one evidence passage.
However, Stubley addresses this by teaching:
identifying, based at least in part on the search, at least one evidence passage that serves as at least one potential link between the first concept and the second concept; (Stubley ¶ 0078-0081: the result of applying one or more search queries constructed by query builder 170 to unstructured data set(s) 140 may be a set of documents and/or passages identified as relevant to a search query and passed to evidence scorer 180. The set of returned documents/passages may be thresholded for relevance in any suitable way ... evaluate the retrieved passages in terms of the strength of supporting evidence that they provide for the extracted answer information as contributing to the best answer to the user's question)
analyzing, using natural language processing, the at least one evidence passage to determine that information included within the at least one evidence passage represents a connection between the first concept and the second concept; (Stubley FIG. 5, ¶ 0124: At act 530, documents containing natural language text may be analyzed, including analyzing one or more passages of text in the documents to determine whether the passage entails any of the hypotheses from the question. Exemplary techniques for entailment analysis are described above. At act 540, in response to determining that a passage entails a question hypothesis, the passage may be identified as providing supporting evidence for the generated answer to the question; Stubley ¶ 0084-0086: the strength of a passage's supporting evidence for answer information for a question portion may be evaluated by determining whether the passage entails a hypothesis corresponding to the question portion ... evidence scorer 180 may score passages based at least in part on the degree to which they entail one or more question hypotheses, and may rank passages based on their scores ... an entailment/contradiction score computed as described above ... may be used as one feature input to a statistical classifier used to score the strength of a passage's supporting evidence for an answer item)
Stubley further teaches generating a query result indicating the at least one evidence passage. (Stubley FIG. 5, ¶ 0123-0124: At act 550, the answer and the passage(s) identified as providing supporting evidence for that answer may be presented to the user in response to the input question. In some embodiments, as discussed above, multiple different passages may be scored based at least in part on the strength of the passages' supporting evidence for the answer to the question, and one or more of the passages may be selected for presentation to the user based on the passages' scores)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the functioning of the evidence passage retrieval of Tripathi with the evidence passage retrieval of Stubley.
In addition, both of the references (Tripathi and Stubley) disclose features that are directed to analogous art, and they are directed to the same field of endeavor, such as question answering interfaces.
Motivation to do so would be to improve the functioning of Tripathi returning search result documents in response to compound queries with the functioning in similar reference Stubley also returning search result documents in response to compound queries but with the improvement of scoring techniques.
Motivation to do so would also be the teaching, suggestion, or motivation for a person of ordinary skill in the art to implement designing a QA system to make intelligent use of both structured and unstructured data sources in its knowledge base as seen in Stubley ¶ 0028.
Regarding claims 2, 9, and 16, Tripathi in view of Stubley teaches:
wherein a potential link of the at least one potential link is a structured relational representation that connects the first concept and the second concept, (Stubley ¶ 0078-0081, see first ¶ 0078: evaluate the retrieved passages in terms of the strength of supporting evidence that they provide for the extracted answer information as contributing to the best answer to the user's question; Stubley ¶ 0079: Evidence scorer 180 may extract answer information from retrieved relevant documents/passages in any suitable way ... extract one or more assertions from a passage to match one or more intent and/or constraint relations from the user's question; Stubley ¶ 0081: evidence scorer 180 may extract the assertion, “Avatar has tall blue aliens,” as being made by the passage. This assertion matches the question constraint “movie X has tall blue aliens” with a specific concept (“Avatar”) replacing the generic/unknown concept (“movie X”) in the constraint, such that the assertion provides candidate answer information for the question constraint)
and wherein the at least one evidence passage includes one or more portions of a knowledge data source of the plurality of knowledge data sources. (Stubley FIG. 5, ¶ 0120-0122: the structured data source(s) may include one or more databases, and in some embodiments, the unstructured data source(s) may include one or more sets of documents containing natural language text [shows plurality of knowledge data sources] … At act 430, one or more first queries may be constructed from the first question portion(s) answerable from the structured data source(s), and may be applied to the structured data source(s) to retrieve first answer information for the first question portion(s) Likewise, one or more second queries may be constructed from the second question portion(s) answerable from the unstructured data source(s), and may be applied to the unstructured data source(s) to retrieve second answer information for the second question portion(s) ... At act 440, answer information from the structured and unstructured data sources may be merged to form an answer to the user's question, and this answer may be presented to the user at act 450. In some embodiments, as discussed above, one or more portions of natural language text from the unstructured data source(s) may be identified as providing evidence that supports answer information retrieved from the unstructured data source(s), and this natural language text (e.g., one or more supporting passages) may be presented to the user in association with the generated answer to the user's question)
Regarding claims 4, 11, and 18, Tripathi in view of Stubley teaches:
wherein the query result includes a portion of the at least one evidence passage that provides evidentiary support for the connection between the first concept and the second concept. (Stubley FIG. 5, ¶ 0123-0124: At act 550, the answer and the passage(s) identified as providing supporting evidence for that answer may be presented to the user in response to the input question. In some embodiments, as discussed above, multiple different passages may be scored based at least in part on the strength of the passages' supporting evidence for the answer to the question, and one or more of the passages may be selected for presentation to the user based on the passages' scores; see connections between concepts in Stubley ¶ 0081: evidence scorer 180 may extract the assertion, “Avatar has tall blue aliens,” as being made by the passage. This assertion matches the question constraint “movie X has tall blue aliens” with a specific concept (“Avatar”) replacing the generic/unknown concept (“movie X”) in the constraint, such that the assertion provides candidate answer information for the question constraint)
Regarding claims 5, 12, and 19 , Tripathi in view of Stubley teaches:
determining a first score indicating a first strength of the connection between the first concept and the second concept; (Stubley ¶ 0082: evidence scorer 180 may evaluate passages in terms of the strength of the evidence they provide in support of the extracted answer information as contributing to accurately answering the user's question; Stubley ¶ 0085-0086: evidence scorer 180 may score passages based at least in part on the degree to which they entail one or more question hypotheses, and may rank passages based on their scores)
identifying, based at least in part on the search, at least one second evidence passage that serves as at least one second potential link between the first concept and the second concept; (Stubley ¶ 0078-0083; see first Stubley ¶ 0078: the result of applying one or more search queries constructed by query builder 170 to unstructured data set(s) 140 may be a set of documents and/or passages [shows at least one second evidence passage] identified as relevant to a search query and passed to evidence scorer 180. The set of returned documents/passages may be thresholded for relevance in any suitable way ... evaluate the retrieved passages in terms of the strength of supporting evidence that they provide for the extracted answer information as contributing to the best answer to the user's question; see then Stubley ¶ 0083: evidence scorer 180 (or any other suitable component of QA system 100, such as question analyzer 160 or query builder 170) may map the user's question to one or more hypotheses to be tested for entailment against one or more assertions extracted from natural language text passages)
analyzing, using the natural language processing, the at least one second evidence passage to determine that second information included within the at least one second evidence passage represents the connection between the first concept and the second concept; and (Stubley FIG. 5, ¶ 0124: At act 530, documents containing natural language text may be analyzed, including analyzing one or more passages of text in the documents [shows natural language processing] to determine whether the passage entails any of the hypotheses from the question. Exemplary techniques for entailment analysis are described above. At act 540, in response to determining that a passage entails a question hypothesis, the passage may be identified as providing supporting evidence for the generated answer to the question)
including the at least one second evidence passage in the query result. (Stubley FIG. 5, ¶ 0123-0124: At act 550, the answer and the passage(s) [shows at least one second evidence passage] identified as providing supporting evidence for that answer may be presented to the user in response to the input question. In some embodiments, as discussed above, multiple different passages may be scored based at least in part on the strength of the passages' supporting evidence for the answer to the question, and one or more of the passages may be selected for presentation to the user based on the passages' scores)
Regarding claims 6 and 13, Tripathi in view of Stubley teaches:
wherein the at least one potential link includes at least one relational representation that connects the first concept and the second concept, (Stubley ¶ 0078-0081; see first Stubley ¶ 0078: the result of applying one or more search queries constructed by query builder 170 to unstructured data set(s) 140 may be a set of documents and/or passages identified as relevant to a search query and passed to evidence scorer 180. The set of returned documents/passages may be thresholded for relevance in any suitable way ... evaluate the retrieved passages in terms of the strength of supporting evidence that they provide for the extracted answer information as contributing to the best answer to the user's question; see then Stubley ¶ 0081: evidence scorer 180 may extract the assertion, “Avatar has tall blue aliens,” as being made by the passage. This assertion matches the question constraint “movie X has tall blue aliens” with a specific concept (“Avatar”) replacing the generic/unknown concept (“movie X”) in the constraint, such that the assertion provides candidate answer information for the question constraint)
further comprising determining at least one relation cluster by aggregating the at least one relational representation based at least in part on a degree of semantic similarity between the at least one relational representation. (Stubley ¶ 0079: evidence scorer 180 may use concept ID and/or semantic parser annotations from retrieved indexed passages, together with any domain model knowledge about the particular relevance of corresponding section headers, document titles, etc., to extract one or more assertions from a passage to match one or more intent and/or constraint relations from the user's question; Stubley ¶ 0086-0104: Any other suitable features may be used in such a classifier, in addition to or instead of the above entailment/contradiction score feature, some non-limiting examples of which may include: ... Brown Clustering PredArg Matcher: Returns an average of the distance among the terms in a semantic relation match. For example, if there is an exact match between the first arguments of a relation (0) but no match between the second (1), the relation's score may be 0.5)
Claims 3, 7; 10, 14; 17, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Tripathi in view of Stubley in further view of Bagchi et al., U.S. Patent Application Publication No. 2018/0025127 (hereinafter Bagchi).
Regarding claims 3, 10, and 17, Tripathi in view of Stubley teaches all the features with respect to claims 1, 8, and 15 above respectively but does not expressly disclose:
wherein the at least one evidence passage indicates that the first concept causes, or induces, the second concept.
However, Bagchi addresses this by teaching:
wherein the at least one evidence passage indicates that the first concept causes, or induces, the second concept. (Bagchi ¶ 0041: The medical examples found herein illustrates this through answers, confidences, dimensions of evidence, associated evidence passages, and documents where this evidence is found, as well as, reliability of the evidence source ... Examples of queries include (but are not limited to): what clinical conditions are characterized by a set of symptoms?; what is the “differential diagnosis” (a ranked list of diseases) that could potentially cause a set of symptoms, conditions, findings?; Bagchi ¶ 0059-0060: a clinical diagnosis query containing symptoms, findings, family history and demographic information, could generate a series of queries as follows, where the text in the <>characters is replaced by the corresponding concepts found in the case text: “What disease of condition could cause <symptom>?”; “What disease of condition could cause <symptom>and <findings>?; “What disease of condition could cause <symptom>, <findings>and <family history>?; “What disease of condition could cause <symptom>, <findings>, <family history>and <demographics>?; etc. ... The method receives answers from the question-answering system in item 210. For each query submitted, the question-answering system 110 returns a list of answers, their confidences, evidence dimensions, and evidence sources)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the functioning of the evidence scoring of Tripathi as modified with the evidence scoring of Bagchi.
In addition, both of the references (Tripathi as modified and Bagchi) disclose features that are directed to analogous art, and they are directed to the same field of endeavor, such as question answering interfaces.
Motivation to do so would also be the teaching, suggestion, or motivation for a person of ordinary skill in the art to improve hypotheses as seen in Bagchi ¶ 0011.
Regarding claims 7 and 14, Tripathi in view of Stubley teaches:
determining an aggregation confidence associated with a relation cluster of the at least one relation cluster, the aggregation confidence being based at least in part on a … score of a portion of the at least one evidence passage. (Stubley ¶ 0109: answer items may be scored based on the evidence scores (e.g., entailment confidence levels) of their respective supporting passages. In some embodiments, the score of an answer item may depend at least in part on how many different passages or documents support that answer item)
Tripathi in view of Stubley does not expressly disclose a reliability score, taught by Bagchi. (Bagchi ¶ 0041: The medical examples found herein illustrates this through answers, confidences, dimensions of evidence, associated evidence passages, and documents where this evidence is found, as well as, reliability of the evidence source)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the functioning of the evidence scoring of Tripathi as modified with the evidence scoring of Bagchi.
In addition, both of the references (Tripathi as modified and Bagchi) disclose features that are directed to analogous art, and they are directed to the same field of endeavor, such as question answering interfaces.
Motivation to do so would be to improve the functioning of Tripathi as modified scoring answers with the functioning in similar reference Bagchi also scoring answers but with the improvement of a variety of evidence techniques.
Regarding claim 20, Tripathi in view of Stubley teaches all the features with respect to claim 15 above including:
wherein the at least one potential link includes at least one relational representation that connects the first concept and the second concept, (Stubley ¶ 0078-0081; see first Stubley ¶ 0078: the result of applying one or more search queries constructed by query builder 170 to unstructured data set(s) 140 may be a set of documents and/or passages identified as relevant to a search query and passed to evidence scorer 180. The set of returned documents/passages may be thresholded for relevance in any suitable way ... evaluate the retrieved passages in terms of the strength of supporting evidence that they provide for the extracted answer information as contributing to the best answer to the user's question; see then Stubley ¶ 0081: evidence scorer 180 may extract the assertion, “Avatar has tall blue aliens,” as being made by the passage. This assertion matches the question constraint “movie X has tall blue aliens” with a specific concept (“Avatar”) replacing the generic/unknown concept (“movie X”) in the constraint, such that the assertion provides candidate answer information for the question constraint)
wherein the operations further comprise: determining at least one relation cluster by aggregating the at least one relational representation based at least in part on a degree of semantic similarity between the at least one relational representation; and (Stubley ¶ 0079: evidence scorer 180 may use concept ID and/or semantic parser annotations from retrieved indexed passages, together with any domain model knowledge about the particular relevance of corresponding section headers, document titles, etc., to extract one or more assertions from a passage to match one or more intent and/or constraint relations from the user's question; Stubley ¶ 0086-0104: Any other suitable features may be used in such a classifier, in addition to or instead of the above entailment/contradiction score feature, some non-limiting examples of which may include: ... Brown Clustering PredArg Matcher: Returns an average of the distance among the terms in a semantic relation match. For example, if there is an exact match between the first arguments of a relation (0) but no match between the second (1), the relation's score may be 0.5)
determining an aggregation confidence associated with a relation cluster of the at least one relation cluster, the aggregation confidence being based at least in part on a … score of a portion of the at least one evidence passage. (Stubley ¶ 0109: answer items may be scored based on the evidence scores (e.g., entailment confidence levels) of their respective supporting passages. In some embodiments, the score of an answer item may depend at least in part on how many different passages or documents support that answer item)
Tripathi in view of Stubley does not expressly disclose a reliability score, taught by Bagchi. (Bagchi ¶ 0041: The medical examples found herein illustrates this through answers, confidences, dimensions of evidence, associated evidence passages, and documents where this evidence is found, as well as, reliability of the evidence source)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the functioning of the evidence scoring of Tripathi as modified with the evidence scoring of Bagchi.
In addition, both of the references (Tripathi as modified and Bagchi) disclose features that are directed to analogous art, and they are directed to the same field of endeavor, such as question answering interfaces.
Motivation to do so would be to improve the functioning of Tripathi as modified scoring answers with the functioning in similar reference Bagchi also scoring answers but with the improvement of a variety of evidence techniques.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Boguraev et al., U.S. Patent No. 10,614,725 (published April 7, 2020); "Generating Secondary Questions In An Introspective Question Answering System"; see Boguraev col. 8, lines 52-67 describing computing and obtaining confidence in a candidate answer and Boguraev col. 12, line 60-col. 13, line 34 ranking candidate answers, relevant to at least dependent claims 7, 14, and 20 describing confidence being based at least in part on a reliability score of a portion of the at least one evidence passage.
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/J.P.F/Examiner, Art Unit 2153 February 11, 2026
/KAVITA STANLEY/Supervisory Patent Examiner, Art Unit 2153