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Zawartość zarchiwizowana w dniu 2022-12-23

Computer-aided learning of lexical functions

Exploitable results

CALLex is a prototype computer learning tool meant for the study of Russian and German vocabularies on the basis of innovative linguistic technologies, above all on the theory of lexical functions (LF) proposed by I.A. Mel'chuk and the theory of lexical decomposition's proposed by Ju. D. Apresjan. It is patterned after a demo version of similar English-Russian and Russian-English tools developed in the Computational linguistics laboratory of the Institute for Information transmission problems of the Russian Academy of Sciences in 1993-1994 under the supervision of Ju. D. Apresjan. Fundamentally CALLex is composed of Explanatory Combinatorial Dictionaries (ECD' s) of Russian and German turned into a database which stores around two thousand lexical items (a thousand per language) with up to five types of lexicographic information assigned to each item: a) headword, b) analytical definition of its meaning in terms of semantic primitives or some intermediate senses, c) part of speech, d) translation into the other language, e) the set of LF's defined for it, with the specification of the possible values of each LF. A LF is a sufficiently general meaning whose value depends upon the given keyword. Among other things, LF's describe the lexically constrained combinatorial potential of words. CALLex makes use of 97 LF's. Five innovative linguistic games based on the concept of LF's and analytical definitions are offered by CALLex: a) translate the given word into the other language, b) supply the values of LF's for a given word, c) supply the values of LF's for a given word on the basis of a translation equivalent in your mother tongue, d) supply the values of a given LF for all the keywords offered by the computer, e) guess the keyword suiting the definition offered by the computer. Depending on the complexity of LF's all the games are arranged in three levels of difficulty. The computer makes use of a system of quantitatively assessing the user's answers on the basis of the level of difficulty and the quality of the user's answers.

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