Longitudinal Analytics
of Web Archive Data


HYENA: Hierarchical Type Classification for Entity Names

The paper "HYENA: Hierarchical Type Classification for Entity Names" by Mohamed Amir Yosef, Sandro Bauer, Johannes Hoffart, Marc Spaniol and Gerhard Weikum has been accepted for COLING 2012.

Inferring lexical type labels for entity mentions in texts is an important asset for NLP tasks like semantic role labeling and named entity disambiguation (NED). Prior work has focused on flat and relatively small type systems where most entities belong to exactly one type. This paper addresses very fine-grained types organized in a hierarchical taxonomy, with several hundreds of types at different levels. We present HYENA for multi-label hierarchical classification. HYENA exploits gazetteer features and accounts for the joint evidence for types at different levels. Experiments and an extrinsic study on NED demonstrate the practical viability of HYENA.

COLING 2012 homepage