公开(公告)号：US12242525B1

公开(公告)日：2025-03-04

申请号：US18079803

申请日：2022-12-12

Applicant: Amazon Technologies, Inc.

Inventor： Parminder Bhatia ,  Thiruvarul Selvan Senthivel ,  Emine Busra Celikkaya ,  Jeremy Douglas Fehr ,  Arjun Mukhopadhyay ,  Shyam Ramaswamy ,  Arun Kumar Ravi

IPC: G06F16/36 ,  G06F16/33 ,  G06F16/334 ,  G06N20/00 ,  G16H50/20

Abstract: Techniques for ontology linking of unstructured text as a service are described. A service may receive a request to link unstructured text to a standardized ontology, 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 and one or more relationships between entities. The service may perform a search of the standardized ontology to identify a set of similar candidates from the standardized ontology for the detected entities and the one or more relationships, and then rank the set of similar candidates from the standardized ontology according to their similarity to the detected entities within the unstructured text. The output from the service may include a result identifying a highest ranked candidate of the set of similar candidates from the standardized ontology for the detected entities within the unstructured text.

公开(公告)号：US11556579B1

公开(公告)日：2023-01-17

申请号：US16714243

申请日：2019-12-13

Applicant: Amazon Technologies, Inc.

Inventor： Parminder Bhatia ,  Thiruvarul Selvan Senthivel ,  Emine Busra Celikkaya ,  Jeremy Douglas Fehr ,  Arjun Mukhopadhyay ,  Shyam Ramaswamy ,  Arun Kumar Ravi

IPC: G06F16/36 ,  G06F16/33 ,  G16H50/20 ,  G06N20/00

Abstract: Techniques for ontology linking of unstructured text as a service are described. A service may receive a request to link unstructured text to a standardized ontology, 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 and one or more relationships between entities. The service may perform a search of the standardized ontology to identify a set of similar candidates from the standardized ontology for the detected entities and the one or more relationships, and then rank the set of similar candidates from the standardized ontology according to their similarity to the detected entities within the unstructured text. The output from the service may include a result identifying a highest ranked candidate of the set of similar candidates from the standardized ontology for the detected entities within the unstructured text.

公开(公告)号：US11487942B1

公开(公告)日：2022-11-01

申请号：US16437338

申请日：2019-06-11

Applicant: Amazon Technologies, Inc.

Inventor： Thiruvarul Selvan Senthivel ,  Varun Sembium Varadarajan ,  Borui Zhang ,  Tiberiu Mircea Doman ,  Parminder Bhatia ,  Arun Kumar Ravi ,  Mohammed Khalilia ,  Emine Busra Celikkaya

IPC: G06F16/93 ,  G06F40/30 ,  G06F40/295 ,  G06F16/28 ,  G06F16/31 ,  G06N3/04 ,  G06N3/08 ,  G06F40/284

Abstract: 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.