I n a well-structured Lexica] Data B a s e , a number of relations among lexica] entries can he interactively evidenced. The present article examines hyponymy, as an example of paradigmatic relation, and "restriction" relation, as a syntagmatic relation. The theoretical results of their implementation are illustrated.

Many lexical semantic relations, such as the hyponymy relation, can be extracted from text as they occur in detectable syntactic constructions. This paper shows how a hypernym-hyponym based lexicon for Swedish can be created directly from a news paper corpus. An algorithm is presented for building partial hierarchical structures from non domain-specific texts.

Semantic dictionaries are widely used in natural language processing studies. Broad range of methods have been proposed to construct semantic dictionaries until this time. In this study, a brief summary for semantic relation pair extraction is introduced. An overview of selected approaches is given and results are compared to each other for hyponymy, holonymy, and antonymy relations.

As part of a project to construct an interactive program which would encourage children to play with language by building jokes, we developed a lexical database, starting from WordNet. To the existing information about part of speech, synonymy, hyponymy, etc., we have added phonetic representations and phonetic similarity ratings for pairs of words/phrases.

At the present time the distinction between compatible versus incompatible co-hyponyms and polysemy versus homonymy is not expressible in WordNet. We aim to enhance WordNet’s expressiveness, through GL inheritance patterns. Hyponymy will then be reflected in the qualia structures shared by the hyponyms and the hyperonym.

I claim that hyperlinks in Wikipedia entries often correspond to semantic relationships between concepts, described by the entries. This bachelor’s thesis discusses supervised methods to automatically identify new links that correspond to a given relation (hyper-/or hyponymy). Training data is collected by mapping Wikipedia articles to WordNet synsets and then marking links where a relation bet...

This paper describes a method of alignment between the noun part of WordNet and Goi-Taikei’s Ontology. The result of the automatic alignment shows that matching words in Japanese as well as in English is highly efficient in extracting correct matches. Analyses of correct alignments by hand illustrate that, in ontology alignment, it is not always possible to preserve relative relations between c...