As its authors note, Miller et al. (1990), WordNet (WN) is a lexical knowledge base, first developed for English and then adopted for several Western European languages, which was created as a machine-readable dictionary based on psycholinguistic principles. The present study is an attempt to discuss the semiautomatic generation of WNs for languages other than English, a topic of great interest since the existence of such WNs will create the appropriate infrastructure for advanced Information Technology systems. Extending the algorithmic approach introduced in Nikolov, Petrova (2001), we propose a semiautomatic method based on heuristics for the generation of WN type synsets and clusters. The focus is on noun and adjective synsets, since nouns and adjectives have completely different organizations in WN, but verb and adverb synset generation is also addressed. The target language for performing tests will be Romanian. Our approach to WN generation relies on so-called “class methods”, namely it uses as knowledge sources individual entries coming from bilingual dictionaries and WN synsets, but at the same time demonstrates the need to combine such methods with structural ones.
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