Entity Linking for Open Information Extraction

Dutta, Arnab ; Schuhmacher, Michael

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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.

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