The Contribution of Componential Analysis to the Semantic Analysis of a Lexical Field of Ancient Hebrew: Some Concrete Examples From the Lexical Field of the … (original) (raw)

European Journal of Jewish Studies, 2008

Abstract

The aim of the present paper is to highlight the main theoretical features of the semantic methodology known as “componential analysis of meaning” (CA), especially focusing on their heuristic relevance in their application to Ancient Hebrew (AH). The elucidation of the theoretical principles and importance of CA will be carried out with a continuous and concrete reference to meaningful examples from the lexical field (LF) of the substantives of “gift” in Ancient Hebrew. As a derived effect, the present paper will also demonstrate that CA can be considered as a theory that actually produces positive results (viz. problem solving, explanatory coherence as well as innovative data). As far as the future scientific role of CA is concerned, it is in fact crucial to insist on the coherence between CA's theoretical principles, its results and its aims—i.e. to claim that CA is a theory. In this regard, in the final part of this paper I will try to describe briefly what the future challenges for CA could be: I will refer in particular to the opportunity of drawing cultural conclusions in the light of the purely linguistic data that are provided by CA, without necessarily removing it from its structuralist constraints. The present paper will be developed into four specific sections: (a) The first—preliminary—section will briefly describe the main theoretical notions of CA. (b) The second part will focus on the analysis and the explanation of the theoretical grounds and the concrete procedures of CA. (c) The third section will provide specific examples from the LF of the substantives of “gift” in order to show the heuristic relevance of CA, especially in cases when problem solving and explanatory coherence are required. (d) The fourth section will try to illustrate what the future challenges for CA could be.

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