BabelNet: The automatic construction, evaluation and application of a wide-coverage multilingual semantic network

We present an automatic approach to the construction of BabelNet, a very large, wide-coverage multilingual semantic network. Key to our approach is the integration of lexicographic and encyclopedic knowledge from WordNet and Wikipedia. In addition, Machine Translation is applied to enrich the resour...

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Bibliographic Details
Published in:Artificial intelligence 2012-12, Vol.193, p.217-250
Main Authors: Navigli, Roberto, Ponzetto, Simone Paolo
Format: Article
Language:English
Subjects:
Algorithmics. Computability. Computer arithmetics
Applied sciences
Artificial intelligence
Computer science
control theory
systems
Exact sciences and technology
Graph algorithms
Information retrieval. Graph
Knowledge acquisition
Semantic networks
Speech and sound recognition and synthesis. Linguistics
Theoretical computing
Word sense disambiguation
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Summary:We present an automatic approach to the construction of BabelNet, a very large, wide-coverage multilingual semantic network. Key to our approach is the integration of lexicographic and encyclopedic knowledge from WordNet and Wikipedia. In addition, Machine Translation is applied to enrich the resource with lexical information for all languages. We first conduct in vitro experiments on new and existing gold-standard datasets to show the high quality and coverage of BabelNet. We then show that our lexical resource can be used successfully to perform both monolingual and cross-lingual Word Sense Disambiguation: thanks to its wide lexical coverage and novel semantic relations, we are able to achieve state-of the-art results on three different SemEval evaluation tasks.
ISSN:0004-3702
1872-7921
DOI:10.1016/j.artint.2012.07.001