Abstract

The presented work is one of the first linguosynergetically oriented stages of the research on coding semantic potential of nouns in relation to category of gender and initial letters of their alphabetical order in explanatory dictionaries of German, namely with initial letters A; B, C, G, H, I in the Duden explanatory dictionary of German. Deutsches Universalwörterbuch. The statement that the driving factor of language development is the synergetic law of making the least effort and conservation of language energy is methodologically important in the study. In a synergistic sense, the author draws parallels between the dictionary as a representation of linguistic generalization about the structured amount of knowledge of learned extraverbal reality and mental lexicon, which is not an arbitrary accumulation of contributions, but is a structured hierarchical system of such contributions. In the synergetic sense, lexical units and their meanings at the linguistic level contain encoded structured information. The linguosynergetic approach of the research applied in this article assumes that language as a self-regulating system under the influence of external energy and information has developed a mechanism for encoding information-semantic volume of nouns in correlation with their grammatical gender and initial letters of their alphabetical order in German. The results obtained on the basis of synergetic-quantitative approach are extrapolated to the linguosynergetic model of self-organization of noun naming according to the principle of minimization of effort, which directs coding of semantic volume of polysemic or monosemic nouns to language economy and minimization of lexical effort of a person. It is proven that since the closest distances in the lexical structure of a word at the language level are the closest in comparison with the knowledge structures of the mental lexicon of a person, then the self-regulating language system under the influence of external energy and information launches mechanisms to optimize the volume of the monosemic model of nouns with one meaning and the semantic volume of the polysemic model with meanings that are closest to the main meaning in the hierarchically structured chain of a polysemous word at the dictionary level.

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