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HYENA-live: Fine-Grained Online Entity Type Classification from Natural-language Text

The paper "HYENA-live: Fine-Grained Online Entity Type Classification from Natural-language Text" by Mohamed Amir Yosef, Sandro Bauer, Johannes Hoffart, Marc Spaniol and Gerhard Weikum has been accepted for the ACL 2013 demo track.

Recent research has shown progress in achieving high-quality, very fine-grained type classification in hierarchical taxonomies. Within such a multi-level type hierarchy with several hundreds of types at different levels, many entities naturally belong to multiple types. In order to achieve high-precision in type classification, current approaches are either limited to certain domains or require time consuming multistage computations. As a consequence, existing systems are incapable of performing ad-hoc type classification on arbitrary input texts. In this demo, we present a novel Web-based tool that is able to perform domain independent entity type classification under real time conditions. Due to its efficient implementation and compacted feature representation, the system is able to process text inputs on-the-fly by achieving equally high precision as leading state-of-the-art implementations. Our system offers an online interface where natural-language text can be inserted, which returns lexical type labels for entity mentions. Further the user interface allows users to explore the types assigned to text mentions by visualizing and navigating along the type-hierarchy.

ACL 2013 homepage