In this paper we propose an instance based method for lexical entailment and apply it to automatic ontology population from text. The approach is fully unsupervised and based on kernel methods. We demonstrate the effectiveness of our technique largely surpassing both the random and most frequent baselines and outperforming current state-of-the-art unsupervised approaches on a benchmark ontology available in the literature.
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Titolo: | Instance Based Lexical Entailment for Ontology Population |
Autori: | |
Data di pubblicazione: | 2007 |
Abstract: | In this paper we propose an instance based method for lexical entailment and apply it to automatic ontology population from text. The approach is fully unsupervised and based on kernel methods. We demonstrate the effectiveness of our technique largely surpassing both the random and most frequent baselines and outperforming current state-of-the-art unsupervised approaches on a benchmark ontology available in the literature. |
Handle: | http://hdl.handle.net/11582/3380 |
Appare nelle tipologie: | 4.1 Contributo in Atti di convegno |
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