Knowledge-rich Word Sense Disambiguation Rivaling Supervised Systems
|Knowledge-rich Word Sense Disambiguation Rivaling Supervised Systems|
|Author(s)||Roberto Navigli Simone Ponzetto|
|Published in||Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics (ACL 2010), Uppsala, Sweden|
|Keyword(s)||wikipedia, word sense disambiguation, knowledge acquisition|
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Knowledge-rich Word Sense Disambiguation Rivaling Supervised Systems is a 2010 conference paper by Roberto Navigli Simone Ponzetto and published in Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics (ACL 2010), Uppsala, Sweden.
One of the main obstacles to high-performance Word Sense Disambiguation (WSD) is the knowledge acquisition bottleneck. In this paper, we present a methodology to automatically extend WordNet with large amounts of semantic relations from an encyclopedic resource, namely Wikipedia. We show that, when provided with a vast amount of high-quality semantic relations, simple knowledge-lean disambiguation algorithms compete with state-of-the-art supervised WSD systems in a coarse-grained all-words setting and outperform them on gold-standard domain-specific datasets.
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