METHODS FOR GENERATING NATURAL LANGUAGE PROCESSING SYSTEMS

METHODS FOR GENERATING NATURAL LANGUAGE PROCESSING SYSTEMS

Methods are presented for generating a natural language model. The method may comprise: ingesting training data representative of documents to be analyzed by the natural language model, generating a hierarchical data structure comprising at least two topical nodes within which the training data is t...

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Hauptverfasser: Hinrichs, Martha G, Brenier, Jason, Casban, Michelle, Saxena, Tripti, Nunez, Edgar, Schnoebelen, Tyler, King, Gary C, Sarin, Ujjwal, Gilchrist-Scott, Andrew, Callahan, Brendan D, Most, Haley, Mechanic, Ross, Erle, Schuyler D, Nair, Aneesh, Walker, Christopher, Tepper, Paul A, Luger, Sarah K, Basavaraj, Veena, Munro, Robert J, Long, Jessica D, Robinson, James B
Format: Patent
Sprache:eng
Schlagworte:
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES
ELECTRIC DIGITAL DATA PROCESSING
PHYSICS
SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR
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Zusammenfassung:Methods are presented for generating a natural language model. The method may comprise: ingesting training data representative of documents to be analyzed by the natural language model, generating a hierarchical data structure comprising at least two topical nodes within which the training data is to be subdivided into by the natural language model, selecting a plurality of documents among the training data to be annotated, generating an annotation prompt for each document configured to elicit an annotation about said document indicating which node among the at least two topical nodes said document is to be classified into, receiving the annotation based on the annotation prompt; and generating the natural language model using an adaptive machine learning process configured to determine patterns among the annotations for how the documents in the training data are to be subdivided according to the at least two topical nodes of the hierarchical data structure.