Abstract: This disclosure enables various technologies that can (1) learn new synonyms for a given concept without manual curation techniques, (2) relate (e.g., map) some, many, most, or all raw named entity recognition outputs (e.g., “United States”, “United States of America”) to ontological concepts (e.g., ISO-3166 country code: “USA”), (3) account for false positives from a prior named entity recognition process, or (4) aggregate some, many, most, or all named entity recognition results from machine learning or rules based approaches to provide a best of breed hybrid approach (e.g., synergistic effect).
Type:
Grant
Filed:
February 5, 2021
Date of Patent:
January 7, 2025
Assignee:
Tellic LLC
Inventors:
Richard Edward Wendell, Eric Tanalski, Henry Edward Crosby, III, Loren Lee Chen, Paul Ton, Jake Rubenstein
Abstract: This disclosure enables various technologies that can (1) learn new synonyms for a given concept without manual curation techniques, (2) relate (e.g., map) some, many, most, or all raw named entity recognition outputs (e.g., “United States”, “United States of America”) to ontological concepts (e.g., ISO-3166 country code: “USA”), (3) account for false positives from a prior named entity recognition process, or (4) aggregate some, many, most, or all named entity recognition results from machine learning or rules based approaches to provide a best of breed hybrid approach (e.g., synergistic effect).
Type:
Grant
Filed:
October 29, 2020
Date of Patent:
August 13, 2024
Assignee:
Tellic LLC
Inventors:
Richard Edward Wendell, Eric Tanalski, Christopher Russel Sipola, Michael Stanley, Henry Edward Crosby, Loren Lee Chen, Paul Ton