Multi-word Entity Classification in a Highly Multilingual Environment

WS 2017 Sophie ChesneyGuillaume JacquetRalf SteinbergerJakub Piskorski

This paper describes an approach for the classification of millions of existing multi-word entities (MWEntities), such as organisation or event names, into thirteen category types, based only on the tokens they contain. In order to classify our very large in-house collection of multilingual MWEntities into an application-oriented set of entity categories, we trained and tested distantly-supervised classifiers in 43 languages based on MWEntities extracted from BabelNet... (read more)

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