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公开(公告)号：US20200334418A1
公开(公告)日：2020-10-22
申请号：US16916248
申请日：2020-06-30
IPC分类号： G06F40/30 , G06N20/00 , G06F40/205 , G06F40/295 , G06F40/211
摘要： Disclosed herein is computer technology that applies natural language processing (NLP) techniques to training data to generate information used to train a natural language generation (NLG) system to produce output that stylistically resembles the training data. In this fashion, the NLG system can be readily trained with training data supplied by a user so that the NLG system is adapted to produce output that stylistically resembles such training data. In an example, an NLP system detects a plurality of linguistic features in the training data. These detected linguistic features are then aggregated into a specification data structure that is arranged for training the NLG system to produce natural language output that stylistically resembles the training data. Parameters in the specification data structure can be linked to objects in an ontology used by the NLG system to facilitate the training of the NLG system based on the detected linguistic features.
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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：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：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：US11521079B2
公开(公告)日：2022-12-06
申请号：US16686756
申请日：2019-11-18
发明人： Nathan Nichols , Michael Justin Smathers , Lawrence Birnbaum , Kristian Hammond , Lawrence E. Adams
摘要： Method and Apparatus for Triggering the Automatic Generation of Narratives Artificial intelligence methods and systems for triggering the generation of narratives are disclosed. Specific embodiments relate to real-time evaluation and automated generation of narrative stories based on received data. For example, data can be tested against data representative of a plurality of story angles to determine whether a narrative story incorporating one or more such story angles is to be automatically generated.
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公开(公告)号：US10706236B1
公开(公告)日：2020-07-07
申请号：US16444649
申请日：2019-06-18
IPC分类号： G06F17/27 , G06F40/30 , G06N20/00 , G06F40/205 , G06F40/295 , G06F40/211 , G10L15/06 , G10L15/22 , G06F40/279 , G10L15/18 , G06F40/268 , G06F40/56
摘要： Applied Artificial Intelligence Technology for Using Natural Language Processing and Concept Expression Templates To Train a Natural Language Generation System Disclosed herein is computer technology that applies natural language processing (NLP) techniques to training data to generate information used to train a natural language generation (NLG) system to produce output that stylistically resembles the training data. In this fashion, the NLG system can be readily trained with training data supplied by a user so that the NLG system is adapted to produce output that stylistically resembles such training data. In an example, an NLP system detects a plurality of linguistic features in the training data. These detected linguistic features are then aggregated into a specification data structure that is arranged for training the NLG system to produce natural language output that stylistically resembles the training data. Parameters in the specification data structure can be linked to objects in an ontology used by the NLG system to facilitate the training of the NLG system based on the detected linguistic features.
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公开(公告)号：US11341330B1
公开(公告)日：2022-05-24
申请号：US16744562
申请日：2020-01-16
IPC分类号： G06F40/284 , G06F40/56 , G06F40/44 , G06N20/00 , G06K9/62 , G06F40/237 , G06F40/216
摘要： Disclosed herein is computer technology that provides adaptive mechanisms for learning concepts that are expressed by natural language sentences, and then applies this learning to appropriately classify new natural language sentences with the relevant concept that they express. The computer technology can also discover the uniqueness of terms within a training corpus, and sufficiently unique terms can be flagged for the user for possible updates to an ontology for the system.
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公开(公告)号：US11042713B1
公开(公告)日：2021-06-22
申请号：US16444748
申请日：2019-06-18
IPC分类号： G06F40/56 , G06N20/00 , G06F40/30 , G06F40/253
摘要： Disclosed herein is computer technology that applies natural language processing (NLP) techniques to training data to generate information used to train a natural language generation (NLG) system to produce output that stylistically resembles the training data. In this fashion, the NLG system can be readily trained with training data supplied by a user so that the NLG system is adapted to produce output that stylistically resembles such training data. In an example, an NLP system detects a plurality of linguistic features in the training data. These detected linguistic features are then aggregated into a specification data structure that is arranged for training the NLG system to produce natural language output that stylistically resembles the training data. Parameters in the specification data structure can be linked to objects in an ontology used by the NLG system to facilitate the training of the NLG system based on the detected linguistic features.
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公开(公告)号：US11030408B1
公开(公告)日：2021-06-08
申请号：US16277006
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： G06F40/295 , G06F40/211 , G06F40/268 , G06F40/30
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：US20200082276A1
公开(公告)日：2020-03-12
申请号：US16686756
申请日：2019-11-18
发明人： Nathan Nichols , Michael Justin Smathers , Lawrence Birnbaum , Kristian Hammond , Lawrence E. Adams
摘要： Method and Apparatus for Triggering the Automatic Generation of Narratives Artificial intelligence methods and systems for triggering the generation of narratives are disclosed. Specific embodiments relate to real-time evaluation and automated generation of narrative stories based on received data. For example, data can be tested against data representative of a plurality of story angles to determine whether a narrative story incorporating one or more such story angles is to be automatically generated.
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