Toward Never Ending Language Learning

Justin Betteridge, Andrew Carlson, Sue Ann Hong, Estevam R. Hruschka, Edith L. M. Law, Tom M. Mitchell, and Sophie H. Wang

We report research toward a never-ending language learning system, focusing on a first implementation which learns to classify occurrences of noun phrases according to lexical categories such as "city" and "university." Our experiments suggest that the accuracy of classifiers produced by semi-supervised learning can be improved by coupling the learning of multiple classes based on background knowledge about relationships between the classes (e.g., "university" is mutually exclusive of "company", and is a subset of "organization").

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