Abstract
In the last years, basic NLP tasks: NER, WSD, relation extraction, etc. have been configured for Semantic Web tasks including ontology learning, linked data population, entity resolution, NL querying to linked data, etc. Some assessment of the state of art of existing Knowledge Extraction (KE) tools when applied to the Semantic Web is then desirable. In this paper we describe a landscape analysis of several tools, either conceived specifically for KE on the Semantic Web, or adaptable to it, or even acting as aggregators of extracted data from other tools. Our aim is to assess the currently available capabilities against a rich palette of ontology design constructs, focusing specifically on the actual semantic reusability of KE output. © 2013 Springer-Verlag Berlin Heidelberg.
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CITATION STYLE
Gangemi, A. (2013). A comparison of knowledge extraction tools for the semantic web. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7882 LNCS, pp. 351–366). Springer Verlag. https://doi.org/10.1007/978-3-642-38288-8_24
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