Learning Rules for Identifying Hypernyms in Machine Readable Dictionaries 


Vol. 13,  No. 2, pp. 171-178, Apr.  2006
10.3745/KIPSTB.2006.13.2.171


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  Abstract

Most approaches for extracting hypernyms of a noun from its definitions in an MRD rely on lexical patterns compiled by human experts. Not only these approaches require high cost for compiling lexical patterns but also it is very difficult for human experts to compile a set of lexical patterns with a broad-coverage because in natural languages there are various expressions which represent same concept. To alleviate these problems, this paper proposes a new method for extracting hypernyms of a noun from its definitions in an MRD. In proposed approach, we use only syntactic (part-of-speech) patterns instead of lexical patterns in identifying hypernyms to reduce the number of patterns with keeping their coverage broad. Our experiment has shown that the classification accuracy of the proposed method is 92.37% which is significantly much better than that of previous approaches.

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[IEEE Style]

S. H. Choi and H. R. Park, "Learning Rules for Identifying Hypernyms in Machine Readable Dictionaries," The KIPS Transactions:PartB , vol. 13, no. 2, pp. 171-178, 2006. DOI: 10.3745/KIPSTB.2006.13.2.171.

[ACM Style]

Seon Hwa Choi and Hyuk Ro Park. 2006. Learning Rules for Identifying Hypernyms in Machine Readable Dictionaries. The KIPS Transactions:PartB , 13, 2, (2006), 171-178. DOI: 10.3745/KIPSTB.2006.13.2.171.

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