Information extraction from Wikipedia using pattern learning

Miháltz, Márton: Information extraction from Wikipedia using pattern learning. Acta cybernetica, (19) 4. pp. 677-694. (2010)

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Abstract

In this paper we present solutions for the crucial task of extracting structured information from massive free-text resources, such as Wikipedia, for the sake of semantic databases serving upcoming Semantic Web technologies. We demonstrate both a verb frame-based approach using deep natural language processing techniques with extraction patterns developed by human knowledge experts and machine learning methods using shallow linguistic processing. We also propose a method for learning verb frame-based extraction patterns automatically from labeled data. We show that labeled training data can be produced with only minimal human effort by utilizing existing semantic resources and the special characteristics of Wikipedia. Custom solutions for named entity recognition are also possible in this scenario. We present evaluation and comparison of the different approaches for several different relations.

Item Type: Article
Event Title: Conference on Hungarian Computational Linguistics, 7., 2010, Szeged
Journal or Publication Title: Acta cybernetica
Date: 2010
Volume: 19
Number: 4
Page Range: pp. 677-694
ISSN: 0324-721X
Language: angol
Uncontrolled Keywords: Természettudomány, Informatika, Nyelvtudomány
Additional Information: Bibliogr.: p. 692-694.; Abstract
Date Deposited: 2016. Oct. 15. 12:24
Last Modified: 2018. Jun. 06. 12:36
URI: http://acta.bibl.u-szeged.hu/id/eprint/12888

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