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Conference Paper

LEILA: Learning to Extract Information by Linguistic Analysis

MPS-Authors
http://pubman.mpdl.mpg.de/cone/persons/resource/persons45572

Suchanek,  Fabian M.
Databases and Information Systems, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons44668

Ifrim,  Georgiana
Databases and Information Systems, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons45720

Weikum,  Gerhard
Databases and Information Systems, MPI for Informatics, Max Planck Society;

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Citation

Suchanek, F. M., Ifrim, G., & Weikum, G. (2006). LEILA: Learning to Extract Information by Linguistic Analysis. In Proceedings of the 2nd Workshop on Ontology Learning and Population (OLP2) @COLING/ACL 2006 (pp. 18-25). Stroudsburg, PA, USA: ACL.


Cite as: http://hdl.handle.net/11858/00-001M-0000-000F-2358-0
Abstract
One of the challenging tasks in the context of the Semantic Web is to automatically extract instances of binary relations from Web documents - for example all pairs of a person and the corresponding birthdate. In this paper, we present LEILA, a system that can extract instances of arbitrary given binary relations from natural language Web documents - without human interaction. Different from previous approaches, LEILA uses a deep syntactic analysis. This results in consistent improvements over comparable systems (such as e.g. Snowball or TextToOnto).