Information extraction from Wikipedia using pattern learning

Miháltz Márton: Information extraction from Wikipedia using pattern learning. In: 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
Journal or Publication Title: Acta cybernetica
Date: 2010
Volume: 19
Number: 4
ISSN: 0324-721X
Page Range: pp. 677-694
Language: English
Place of Publication: Szeged
Event Title: Conference on Hungarian Computational Linguistics (7.) (2010) (Szeged)
Related URLs: http://acta.bibl.u-szeged.hu/38530/
Uncontrolled Keywords: Számítástechnika, Nyelvészet - számítógép alkalmazása
Additional Information: Bibliogr.: p. 692-694. ; összefoglalás angol nyelven
Subjects: 01. Natural sciences
01. Natural sciences > 01.02. Computer and information sciences
06. Humanities
06. Humanities > 06.02. Languages and Literature
Date Deposited: 2016. Oct. 15. 12:24
Last Modified: 2022. Jun. 17. 11:10
URI: http://acta.bibl.u-szeged.hu/id/eprint/12888

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