According to principles described herein, unsupervised statistical models, semi-supervised data models, and HITL methods are combined to create a text normalization system that is both robust and trainable with a minimum of human intervention. This system can be applied to data from multiple sources to standardize text for insertion into knowledge bases, machine learning model training and evaluation corpora, and analysis tools and databases
A SYSTEM AND METHOD OF COMBINING STATISTICAL MODELS, DATA MODELS, AND HUMAN-IN-THE-LOOP FOR TEXT NORMALIZATION