One of the problems in converting a conventional (human-oriented) explanatory dictionary into a semantic database intended for the use in automatic reasoning systems is that such a database should not contain any cycles in its definitions, while the traditional dictionaries usually contain them. The cycles can be eliminated by declaring some words "primitive" (having no definition) while all other words are defined in terms of these ones. A method for detecting the cycles in definitions and selecting a minimal (though not the smallest) defining vocabulary is presented. Different strategies for selecting the words for the defining vocabulary are discussed and experimental data for a real dictionary are presented.
Gelbukh et al. proposed a method for detecting cycles in word definitions and selecting primitive words REF .
Automatic selection of defining vocabulary in an explanatory dictionary
In A. Gelbukh (Ed.), Computational Linguistics and Intelligent Text Processing, CICLing-2002. Lecture Notes in Computer Science N 2276
Computer Science