Fiammetta Namer: Morphologic productivity, representativity and base complexity: the MoQuête system In this paper we propose to describe a corpus processor that can be used to prepare and create lexical databases for French, and whose exploitation is more particularly oriented towards morphological parsing. This processor, called MoQuête (Morphology & Queries), applies on a lexical database (LDB) whose realization is the results of the following steps: recover online corpora, tag them, lemmatize them, and submit them to derivational morphological parsing. Starting from the experiment described for dutch in (Krott & ah, 1999), we illustrate the MoQuête behavior with the presentation of a série of measures, performed from a 27 millions tokens LDB obtained from newspapers online corpora, and meant to evaluate the link between the quantitative morphologic productivity and the representativity of morphologic rules, in the frame of complex lexical units with a complex base.