SYSTEMS AND METHODS FOR IDENTIFYING A RISK OF IMPLIEDLY OVERRULED CONTENT BASED ON CITATIONALLY RELATED CONTENT
Patent №
US 11,615,492
Granted
2023-03-28
Filed 2019
Owner
THOMSON REUTERS CANADA LIMITED
+4 more
Lab
—
AI components
7
ml · nlp · vision · speech · kr · planning · hardware
Assignment
Recorded
Dataset
AIPD
2023_r1 edition
Application
16411809
The present disclosure relates to systems and methods for analyzing citationally related content and identifying, based on the analysis, a risk of impliedly overruled content. Embodiments provide for receiving case law data from a document source, for extracting a case triple that includes a first case overruling or abrogating a second case, and a third case citationally related to the second case. Features may be generated from case triple, such as natural processing language features comparing the language in the various cases of the triple, and feeding the generated features to a main classifier. In embodiments, the main classifier classifies the case triple into a class indicating the risk probability that the second case is impliedly overruled by the first case.
AI classification
Ownership
THOMSON REUTERS CANADA LIMITED
assignment · 523280828
THOMSON REUTERS HOLDINGS INC.
assignment · 523290228
WEST PUBLISHING CORPORATION
assignment · 523290384
THOMSON REUTERS GLOBAL RESOURCES UNLIMITED COMPANY
assignment · 523290448
THOMSON REUTERS ENTERPRISE CENTRE GMBH
assignment · 523400914
Assignors
BROOKE, JULIAN, MADAN, KANIKA, ALONSO, HECTOR MARTINEZ, FAZLY, AFSANEH, CUSTIS, TONYA, MOULINIER, ISABELLE, MCELVAIN, GAYLE, ERICKSON, DIANE
On an employer assignment, the assignors are typically the inventors.