Service architecture for entity and relationship detection in unstructured text
Techniques for entity and relationship detect from unstructured text as a service are described. A service may receive a request to identify entities within a provided unstructured text element, and the service may segment and tokenize the unstructured text and send the result to multiple services i...
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creator | Bhatia, Parminder Zhang, Borui Doman, Tiberiu Mircea Ravi, Arun Kumar Khalilia, Mohammed Senthivel, Thiruvarul Selvan Sembium Varadarajan, Varun Celikkaya, Emine Busra |
description | Techniques for entity and relationship detect from unstructured text as a service are described. A service may receive a request to identify entities within a provided unstructured text element, and the service may segment and tokenize the unstructured text and send the result to multiple services implementing multiple deep machine learning models trained to identify particular entities. The service may send additional requests to an additional service or services implementing additional deep machine learning models to identify relationships between detected attributes and ones of the detected entities. The outputs from all services can be analyzed and consolidated into a single result that identifies the entities, any attributes of the entities, and confidence scores indicating the confidence in each detected entity. |
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subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING ELECTRIC DIGITAL DATA PROCESSING PHYSICS |
title | Service architecture for entity and relationship detection in unstructured text |
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