Abstract: Systems and methods for automatically detecting annotation discrepancies in annotated training data samples and repairing the annotated training data samples for a machine learning-based automated dialogue system include evaluating a corpus of a plurality of distinct training data samples; identifying one or more of a slot span defect and a slot label defect of a target annotated slot span of a target training data sample of the corpus based on the evaluation; and automatically correcting one or more annotations of the target annotated slot span based on the identified one or more of the slot span defect and the slot label defect.
Type:
Grant
Filed:
June 8, 2020
Date of Patent:
February 23, 2021
Assignee:
Clinic, Inc.
Inventors:
Stefan Larson, Anish Mahendran, Parker Hill, Jonathan K. Kummerfeld, Michael A. Laurenzano, Lingjia Tang, Jason Mars