Zero-shot entity linking based on symbolic information

US12001794B2 · kind B2 · utility

Assignee

• International Business Machines Corporation · US

Inventors

• Dinesh Khandelwal · Indore, IN
• G P Shrivatsa Bhargav · Bengaluru, IN
• Saswati Dana · Bengaluru, IN
• Dinesh Garg · Beawar, IN
• Pavan Kapanipathi Bangalore · Yorktown Heights, US
• Salim Roukos · Los Angeles, US
• Alexander Gray · Yonkers, US
• L. Venkata Subramaniam · New Delhi, IN

Key dates

• Filing date: Jan 14, 2022
• Grant date: Jun 4, 2024
• Expiry date: Dec 11, 2042

Classification

• Technology area (CPC G): Physics
• CPC primary: G06N20/00
• WIPO field: Computer technology
• WIPO sector: Electrical engineering

Abstract

Methods, systems, and computer program products for zero-shot entity linking based on symbolic information are provided herein. A computer-implemented method includes obtaining a knowledge graph comprising a set of entities and a training dataset comprising text samples for at least a subset of the entities in the knowledge graph; training a machine learning model to map an entity mention substring of a given sample of text to one corresponding entity in the set of entities, wherein the machine learning model is trained using a multi-task machine learning framework using symbolic information extracted from the knowledge graph; and mapping an entity mention substring of a new sample of text to one of the entities in the set using the trained machine learning model.