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AAAI
2008

Automatic Semantic Relation Extraction with Multiple Boundary Generation

13 years 6 months ago
Automatic Semantic Relation Extraction with Multiple Boundary Generation
This paper addresses the task of automatic classification of semantic relations between nouns. We present an improved WordNet-based learning model which relies on the semantic information of the constituent nouns. The representation of each noun's meaning captures conceptual features which play a key role in the identification of the semantic relation. We report substantial improvements over previous WordNet-based methods on the 2007 SemEval data. Moreover, our experiments show that WordNet's IS-A hierarchy is better suited for some semantic relations compared with others. We also compute various learning curves and show that our model does not need a large number of training examples.
Brandon Beamer, Alla Rozovskaya, Roxana Girju
Added 02 Oct 2010
Updated 02 Oct 2010
Type Conference
Year 2008
Where AAAI
Authors Brandon Beamer, Alla Rozovskaya, Roxana Girju
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