Patents by Inventor Nathan D. Nichols
Nathan D. Nichols has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 11954445Abstract: 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.Type: GrantFiled: December 22, 2022Date of Patent: April 9, 2024Assignee: Narrative Science LLCInventors: Nathan D. Nichols, Andrew R. Paley, Maia Lewis Meza, Santiago Santana
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Patent number: 11921985Abstract: The exemplary embodiments describe, inter alia, an apparatus comprising: a processor configured to (1) generate a plurality of graphical user interfaces (GUIs) for interaction with a user to support configuration of a narrative story generator to automatically generate a narrative story based on input data, wherein at least one of the GUIs presents content blocks comprising a story outline in a hierarchical structure, (2) evaluate configuration elements of the narrative story generated using imported sample data, and (3) generate narrative stories based on the configuration of the narrative story generator and the input data.Type: GrantFiled: January 10, 2023Date of Patent: March 5, 2024Assignee: Narrative Science LLCInventors: Andrew R. Paley, Nathan D. Nichols, Kristian J. Hammond
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Patent number: 11816435Abstract: 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.Type: GrantFiled: February 15, 2019Date of Patent: November 14, 2023Assignee: Narrative Science Inc.Inventors: Maia Lewis Meza, Clayton Nicholas Norris, Michael Justin Smathers, Daniel Joseph Platt, Nathan D. Nichols
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Publication number: 20230206006Abstract: 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.Type: ApplicationFiled: December 22, 2022Publication date: June 29, 2023Inventors: Nathan D. Nichols, Andrew R. Paley, Maia Lewis Meza, Santiago Santana
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Patent number: 11568148Abstract: 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.Type: GrantFiled: November 7, 2018Date of Patent: January 31, 2023Assignee: Narrative Science Inc.Inventors: Nathan D. Nichols, Andrew R. Paley, Maia Lewis Meza, Santiago Santana
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Patent number: 11561684Abstract: The exemplary embodiments describe, inter alia, an apparatus comprising: a processor configured to (1) generate a plurality of graphical user interfaces (GUIs) for interaction with a user to support configuration of a narrative story generator to automatically generate a narrative story based on input data, wherein at least one of the GUIs presents content blocks comprising a story outline in a hierarchical structure, (2) evaluate configuration elements of the narrative story generated using imported sample data, and (3) generate narrative stories based on the configuration of the narrative story generator and the input data.Type: GrantFiled: January 22, 2019Date of Patent: January 24, 2023Assignee: Narrative Science Inc.Inventors: Andrew R. Paley, Nathan D. Nichols, Kristian J. Hammond
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Patent number: 11562146Abstract: 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.Type: GrantFiled: March 3, 2021Date of Patent: January 24, 2023Assignee: Narrative Science Inc.Inventors: Andrew R. Paley, Nathan D. Nichols, Matthew L. Trahan, Maia Lewis Meza, Michael Tien Thinh Pham, Charlie M. Truong
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Patent number: 11341330Abstract: 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.Type: GrantFiled: January 16, 2020Date of Patent: May 24, 2022Assignee: NARRATIVE SCIENCE INC.Inventors: Michael Justin Smathers, Daniel Joseph Platt, Nathan D. Nichols, Jared Lorince
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Patent number: 11334726Abstract: 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.Type: GrantFiled: June 18, 2019Date of Patent: May 17, 2022Assignee: NARRATIVE SCIENCE INC.Inventors: Daniel Joseph Platt, Nathan D. Nichols, Michael Justin Smathers, Jared Lorince
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Patent number: 11232270Abstract: 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.Type: GrantFiled: June 18, 2019Date of Patent: January 25, 2022Assignee: NARRATIVE SCIENCE INC.Inventors: Daniel Joseph Platt, Nathan D. Nichols, Michael Justin Smathers, Jared Lorince
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Patent number: 11182556Abstract: 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.Type: GrantFiled: February 15, 2019Date of Patent: November 23, 2021Assignee: NARRATIVE SCIENCE INC.Inventors: Maia Lewis Meza, Clayton Nicholas Norris, Michael Justin Smathers, Daniel Joseph Platt, Nathan D. Nichols
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Patent number: 11126798Abstract: 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.Type: GrantFiled: February 15, 2019Date of Patent: September 21, 2021Assignee: NARRATIVE SCIENCE INC.Inventors: Maia Lewis Meza, Clayton Nicholas Norris, Michael Justin Smathers, Daniel Joseph Platt, Nathan D. Nichols
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Patent number: 11068661Abstract: 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.Type: GrantFiled: November 7, 2018Date of Patent: July 20, 2021Assignee: NARRATIVE SCIENCE INC.Inventors: Nathan D. Nichols, Andrew R. Paley, Maia Lewis Meza, Santiago Santana
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Publication number: 20210192144Abstract: 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.Type: ApplicationFiled: March 3, 2021Publication date: June 24, 2021Inventors: Andrew R. Paley, Nathan D. Nichols, Matthew L. Trahan, Maia Lewis Meza, Michael Tien Thinh Pham, Charlie M. Truong
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Patent number: 11042713Abstract: 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.Type: GrantFiled: June 18, 2019Date of Patent: June 22, 2021Assignee: NARRATIVE SCIENC INC.Inventors: Daniel Joseph Platt, Nathan D. Nichols, Michael Justin Smathers, Jared Lorince
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Patent number: 11030408Abstract: 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.Type: GrantFiled: February 15, 2019Date of Patent: June 8, 2021Assignee: NARRATIVE SCIENCE INC.Inventors: Maia Lewis Meza, Clayton Nicholas Norris, Michael Justin Smathers, Daniel Joseph Platt, Nathan D. Nichols
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Patent number: 10990767Abstract: Applied Artificial Intelligence Technology for Adaptive Natural Language Understanding 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.Type: GrantFiled: January 16, 2020Date of Patent: April 27, 2021Assignee: NARRATIVE SCIENCE INC.Inventors: Michael Justin Smathers, Daniel Joseph Platt, Nathan D. Nichols, Jared Lorince
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Patent number: 10943069Abstract: 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.Type: GrantFiled: July 27, 2018Date of Patent: March 9, 2021Assignee: NARRATIVE SCIENCE INC.Inventors: Andrew R. Paley, Nathan D. Nichols, Matthew L. Trahan, Maia Lewis Meza, Michael Tien Thinh Pham, Charlie M. Truong
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Publication number: 20200334418Abstract: 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.Type: ApplicationFiled: June 30, 2020Publication date: October 22, 2020Inventors: Daniel Joseph Platt, Nathan D. Nichols, Michael Justin Smathers, Jared Lorince
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Patent number: 10755046Abstract: 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.Type: GrantFiled: February 15, 2019Date of Patent: August 25, 2020Assignee: NARRATIVE SCIENCE INC.Inventors: Maia Lewis Meza, Clayton Nicholas Norris, Michael Justin Smathers, Daniel Joseph Platt, Nathan D. Nichols