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Title: Multilingual ontology acquisition from multiple MRDs
Authors: Nichols, Eric
Flickinger, Dan
Bond, Francis
Tanaka, Takaaki
Fujita, Sanae
Keywords: DRNTU::Humanities::Linguistics::Sociolinguistics::Computational linguistics
Issue Date: 2006
Source: Nichols, E., Bond, F., Tanaka, T., Fujita, S. & Flickinger, D. (2006). Multilingual Ontology Acquisition from Multiple MRDs. Proceedings of the 2nd Workshop on Ontology Learning and Population, Sydney, pp.10-17.
Abstract: In this paper, we outline the development of a system that automatically constructs ontologies by extracting knowledge from dictionary definition sentences using Robust Minimal Recursion Semantics (RMRS). Combining deep and shallow parsing resource through the common formalism of RMRS allows us to extract ontological relations in greater quantity and quality than possible with any of the methods independently. Using this method, we construct ontologies from two different Japanese lexicons and one English lexicon. We then link them to existing, handcrafted ontologies, aligning them at the word-sense level. This alignment provides a representative evaluation of the quality of the relations being extracted. We present the results of this ontology construction and discuss how our system was designed to handle multiple lexicons and languages.
Rights: © 2006 Association for Computational Linguistics. This paper was published in Proceedings of the 2nd Workshop on Ontology Learning and Population and is made available as an electronic reprint (preprint) with permission of Association for Computational Linguistics. The paper can be found at the following official URL:  One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:HSS Conference Papers

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