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Conference Paper

SOFIE: A Self-Organizing Framework for Information Extraction

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

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

http://pubman.mpdl.mpg.de/cone/persons/resource/persons45527

Sozio,  Mauro
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., Sozio, M., & Weikum, G. (2009). SOFIE: A Self-Organizing Framework for Information Extraction. In Proceedings of the 18th World Wide Web Conference (pp. 631-640). New York, NY: ACM.


Cite as: http://hdl.handle.net/11858/00-001M-0000-000F-1950-D
Abstract
This paper presents SOFIE, a system for automated ontology extension. SOFIE can parse natural language documents, extract ontological facts from them and link the facts into an ontology. SOFIE uses logical reasoning on the existing knowledge and on the new knowledge in order to disambiguate words to their most probable meaning, to reason on the meaning of text patterns and to take into account world knowledge axioms. This allows SOFIE to check the plausibility of hypotheses and to avoid inconsistencies with the ontology. The framework of SOFIE unites the paradigms of pattern matching, word sense disambiguation and ontological reasoning in one unified model. Our experiments show that SOFIE delivers high-quality output, even from unstructured Internet documents.