Abstract
Taxonomy structures are important tools in the science of classification of things or concepts, including the principles that underlie such classification. This paper presents an approach to the problem of taxonomy construction from texts focusing on the hyponym-hypernym relation between two terms. Given a set of terms in a particular domain, the approach in this study uses Wikipedia and WordNet as knowledge sources and applies the information extraction methods to analyze and establish the hyponym-hypernym relationship between two terms. Our system is ranked fourth among the participating systems in SemEval-2015 task 17.
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CITATION STYLE
Ceesay, B., & Hou, W. J. (2015). NTNU: An Unsupervised Knowledge Approach for Taxonomy Extraction. In SemEval 2015 - 9th International Workshop on Semantic Evaluation, co-located with the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2015 - Proceedings (pp. 938–943). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/s15-2156
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