| A Workshop on Machine Learning in Natural Language Processing |
Organizers: Shalom Lapin and Ido Dagan |
Global Inference and Learning: Towards Natural Language Understanding
Dan Roth
University of Illinois at Urbana-Champaign
The maturity of machine learning techniques allows us today to learn many low level natural language predicates and generate an appropriate vocabulary over which reasoning methods can be used to make significant progress in natural language understanding. I will describe research on a framework that combines learning and inference. Our Inference with Classifiers approach allows the output of local classifiers for different problem components to be assembled into a whole that reflects global preferences and constraints. Examples will be drawn from ‘wh’ attribution in natural language processing (determining who did what to whom when and where) and textual entailment (determining whether one utterance is a likely consequence of another). |