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1.
公开(公告)号:US20230161970A1
公开(公告)日:2023-05-25
申请号:US18152304
申请日:2023-01-10
发明人: Andrew R. Paley , Nathan D. Nichols , Matthew L. Trahan , Maia Lewis Meza , Michael Tien Thinh Pham , Charlie M. Truong
IPC分类号: G06F40/30 , G06N5/02 , G06F40/295 , G10L17/18
CPC分类号: G06F40/30 , G06N5/02 , G06F40/295 , G10L17/18
摘要: Artificial intelligence (AI) technology can be used in combination with composable communication goal statements to facilitate a user's ability to quickly structure story outlines in a manner usable by an NLG narrative generation system without any need for the user to directly author computer code. Narrative analytics that are linked to communication goal statements can employ a conditional outcome framework that allows the content and structure of resulting narratives to intelligently adapt as a function of the nature of the data under consideration. This
AI technology permits NLG systems to determine the appropriate content for inclusion in a narrative story about a data set in a manner that will satisfy a desired communication goal.-
公开(公告)号:US11126798B1
公开(公告)日:2021-09-21
申请号:US16277003
申请日:2019-02-15
发明人: Maia Lewis Meza , Clayton Nicholas Norris , Michael Justin Smathers , Daniel Joseph Platt , Nathan D. Nichols
IPC分类号: G06F40/56 , H04L12/58 , G06F40/30 , G06F40/211 , G06F40/295
摘要: Disclosed herein is an NLP system that is able to extract meaning from a natural language message using improved parsing techniques. Such an NLP system can be used in concert with an NLG system to interactively interpret messages and generate response messages in an interactive conversational stream. The parsing can include (1) named entity recognition that contextualizes the meanings of words in a message with reference to a knowledge base of named entities understood by the NLP and NLG systems, (2) syntactically parsing the message to determine a grammatical hierarchy for the named entities within the message, (3) reduction of recognized named entities into aggregations of named entities using the determined grammatical hierarchy and reduction rules to further clarify the message's meaning, and (4) mapping the reduced aggregation of named entities to an intent or meaning, wherein this intent/meaning can be used as control instructions for an NLG process.
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公开(公告)号:US10755046B1
公开(公告)日:2020-08-25
申请号:US16277000
申请日:2019-02-15
发明人: Maia Lewis Meza , Clayton Nicholas Norris , Michael Justin Smathers , Daniel Joseph Platt , Nathan D. Nichols
IPC分类号: G06F17/27 , G06F17/21 , G06F40/279 , G06F40/30 , G06F40/211 , G06F40/253
摘要: Disclosed herein is an NLP system that is able to extract meaning from a natural language message using improved parsing techniques. Such an NLP system can be used in concert with an NLG system to interactively interpret messages and generate response messages in an interactive conversational stream. The parsing can include (1) named entity recognition that contextualizes the meanings of words in a message with reference to a knowledge base of named entities understood by the NLP and NLG systems, (2) syntactically parsing the message to determine a grammatical hierarchy for the named entities within the message, (3) reduction of recognized named entities into aggregations of named entities using the determined grammatical hierarchy and reduction rules to further clarify the message's meaning, and (4) mapping the reduced aggregation of named entities to an intent or meaning, wherein this intent/meaning can be used as control instructions for an NLG process.
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公开(公告)号:US10699079B1
公开(公告)日:2020-06-30
申请号:US16047800
申请日:2018-07-27
发明人: Andrew R. Paley , Nathan D. Nichols , Matthew L. Trahan , Maia Lewis Meza , Michael Tien Thinh Pham , Charlie M. Truong
IPC分类号: G06F17/27 , G06F40/30 , G06N5/02 , G06F40/295 , G06F17/21
摘要: Artificial intelligence (AI) technology can be used in combination with composable communication goal statements to facilitate a user's ability to quickly structure story outlines using “analyze” communication goals in a manner usable by an NLG narrative generation system without any need for the user to directly author computer code. This AI technology permits NLG systems to determine the appropriate content for inclusion in a narrative story about a data set in a manner that will satisfy a desired analysis communication goal such that the narratives will express various ideas that are deemed relevant to a given analysis communication goal.
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公开(公告)号:US11816435B1
公开(公告)日:2023-11-14
申请号:US16277004
申请日:2019-02-15
发明人: Maia Lewis Meza , Clayton Nicholas Norris , Michael Justin Smathers , Daniel Joseph Platt , Nathan D. Nichols
IPC分类号: G06F40/00 , G06F40/30 , G06F40/211 , G06F40/295 , G10L15/22 , G10L15/18 , G10L15/183
CPC分类号: G06F40/30 , G06F40/211 , G06F40/295 , G10L15/183 , G10L15/1822 , G10L15/22
摘要: Disclosed herein is an NLP system that is able to extract meaning from a natural language message using improved parsing techniques. Such an NLP system can be used in concert with an NLG system to interactively interpret messages and generate response messages in an interactive conversational stream. The parsing can include (1) named entity recognition that contextualizes the meanings of words in a message with reference to a knowledge base of named entities understood by the NLP and NLG systems, (2) syntactically parsing the message to determine a grammatical hierarchy for the named entities within the message, (3) reduction of recognized named entities into aggregations of named entities using the determined grammatical hierarchy and reduction rules to further clarify the message's meaning, and (4) mapping the reduced aggregation of named entities to an intent or meaning, wherein this intent/meaning can be used as control instructions for an NLG process.
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公开(公告)号:US20210192144A1
公开(公告)日:2021-06-24
申请号:US17191362
申请日:2021-03-03
发明人: Andrew R. Paley , Nathan D. Nichols , Matthew L. Trahan , Maia Lewis Meza , Michael Tien Thinh Pham , Charlie M. Truong
IPC分类号: G06F40/30 , G06N5/02 , G06F40/295
摘要: Artificial intelligence (AI) technology can be used in combination with composable communication goal statements to facilitate a user's ability to quickly structure story outlines in a manner usable by an NLG narrative generation system without any need for the user to directly author computer code. Narrative analytics that are linked to communication goal statements can employ a conditional outcome framework that allows the content and structure of resulting narratives to intelligently adapt as a function of the nature of the data under consideration. This AI technology permits NLG systems to determine the appropriate content for inclusion in a narrative story about a data set in a manner that will satisfy a desired communication goal.
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公开(公告)号:US10943069B1
公开(公告)日:2021-03-09
申请号:US16047837
申请日:2018-07-27
发明人: Andrew R. Paley , Nathan D. Nichols , Matthew L. Trahan , Maia Lewis Meza , Michael Tien Thinh Pham , Charlie M. Truong
IPC分类号: G06F40/30 , G06N5/02 , G06F40/295
摘要: Artificial intelligence (AI) technology can be used in combination with composable communication goal statements to facilitate a user's ability to quickly structure story outlines in a manner usable by an NLG narrative generation system without any need for the user to directly author computer code. Narrative analytics that are linked to communication goal statements can employ a conditional outcome framework that allows the content and structure of resulting narratives to intelligently adapt as a function of the nature of the data under consideration. This AI technology permits NLG systems to determine the appropriate content for inclusion in a narrative story about a data set in a manner that will satisfy a desired communication goal.
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8.
公开(公告)号:US20230206006A1
公开(公告)日:2023-06-29
申请号:US18145193
申请日:2022-12-22
IPC分类号: G06F40/30 , G06N5/022 , G06N20/00 , G06F40/295
CPC分类号: G06F40/30 , G06F40/295 , G06N5/022 , G06N20/00
摘要: Artificial intelligence (AI) technology can be used in combination with composable communication goal statements to facilitate a user’s ability to quickly structure story outlines using “explanation” communication goals in a manner usable by an NLG narrative generation system without any need for the user to directly author computer code. This AI technology permits NLG systems to determine the appropriate content for inclusion in a narrative story about a data set in a manner that will satisfy a desired explanation communication goal such that the narratives will express various ideas that are deemed relevant to a given explanation communication goal.
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公开(公告)号:US11562146B2
公开(公告)日:2023-01-24
申请号:US17191362
申请日:2021-03-03
发明人: Andrew R. Paley , Nathan D. Nichols , Matthew L. Trahan , Maia Lewis Meza , Michael Tien Thinh Pham , Charlie M. Truong
IPC分类号: G06F40/30 , G06N5/02 , G06F40/295 , G10L17/18
摘要: Artificial intelligence (AI) technology can be used in combination with composable communication goal statements to facilitate a user's ability to quickly structure story outlines in a manner usable by an NLG narrative generation system without any need for the user to directly author computer code. Narrative analytics that are linked to communication goal statements can employ a conditional outcome framework that allows the content and structure of resulting narratives to intelligently adapt as a function of the nature of the data under consideration. This AI technology permits NLG systems to determine the appropriate content for inclusion in a narrative story about a data set in a manner that will satisfy a desired communication goal.
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10.
公开(公告)号:US11068661B1
公开(公告)日:2021-07-20
申请号:US16183230
申请日:2018-11-07
IPC分类号: G06F40/30 , G06N5/02 , G06N20/00 , G06F40/295
摘要: Artificial intelligence (AI) technology can be used in combination with composable communication goal statements to facilitate a user's ability to quickly structure story outlines in a manner usable by an NLG narrative generation system without any need for the user to directly author computer code. This AI technology permits attribute structures within an ontology can include an explicit model for the subject attribute, regardless of whether that model is used to compute the value of the subject attribute itself. This explicit model can then be leveraged to support an investigation of drivers of the value for the subject attribute. Narrative analytics that perform driver analysis can then be used to support narrative generation for communication goals relating to explanations, predictions, recommendations, and the like.
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