WoLE 2012 - Unsupervised Extraction and Publication of Linked Entities and Hypernyms
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TitleUnsupervised Extraction and Publication of Linked Entities and Hypernyms
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AuthorsMilan DojchinovskiTomas Kliegr
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Web Engineering Group Department of Information and Knowledge Engineering
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Faculty of Information Technology Czech Technical University in PragueFaculty of Informatics and Statistics
University of Economics, Prague, Czech Republic
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milan.dojchinovski@fit.cvut.cztomas.kliegr@vse.cz
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http://dojchinovski.mkhttps://sites.google.com/site/kliegr/
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AbstractEasy extraction and access to an information from a semi- structured textual documents is still a challenge. In this paper, we present a method for effective extraction of entities as well as a way of publishing such information in a machine-readable RDF/OWL -based format based on the four Linked Data principles. Using our approach the users, as well as the other tools, can share the NLP processed results among each other. We present the architecture of the tool implemented as a web application and an API. We validate our tool on a real dataset, and show the effectiveness of the approach in comparison to other existing NER tools.
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KeywordsNamed Entity Extractors, Linked Data, Link Discovery
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WWWhttp://ner.vse.cz/thd
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