Entity Linking for Open Information Extraction

Preview

PDF
ArnabMichael.pdf - Published
Download (166kB)

URL:	https://ub-madoc.bib.uni-mannheim.de/36671
Additional URL:	https://madata.bib.uni-mannheim.de/65/
URN:	urn:nbn:de:bsz:180-madoc-366716
Document Type:	Conference or workshop publication
Year of publication:	2014
Book title:	Natural Language Processing and Information Systems : 19th International Conference on Applications of Natural Language to Information Systems, NLDB 2014, Montpellier, France, June 18-20, 2014. Proceedings
The title of a journal, publication series:	Lecture Notes in Computer Science
Volume:	8455
Page range:	75-80
Date of the conference:	June 18-20, 2014
Publisher:	Métais, Elisabeth
Place of publication:	Berlin [u.a.]
Publishing house:	Springer
ISBN:	978-3-319-07982-0 , 978-3-319-07983-7
ISSN:	0302-9743 , 1611-3349
Publication language:	English
Institution:	School of Business Informatics and Mathematics > Practical Computer Science II: Artificial Intelligence (Stuckenschmidt 2009-)
Subject:	004 Computer science, internet
Abstract:	Open domain information extraction (OIE) projects like Nell or ReVerb are often impaired by a schema-poor structure. This severely limits their application domain in spite of having web-scale coverage. In this work we try to disambiguate an OIE fact by referring its terms to unique instances from a structured knowledge base, DBpedia in our case. We propose a method which exploits the frequency information and the semantic relatedness of all probable candidate pairs. We show that our combined linking method outperforms a strong baseline.