2010 KnowledgeRichWordSenseDisambigu

From GM-RKB
Jump to navigation Jump to search

Subject Headings:

Notes

Cited By

Quotes

Abstract

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.

References

,

 AuthorvolumeDate ValuetitletypejournaltitleUrldoinoteyear
2010 KnowledgeRichWordSenseDisambiguSimone P. Ponzetto
Roberto Navigli
Knowledge-rich Word Sense Disambiguation Rivaling Supervised Systems2010