Text simplification is the process of reducing the lexical and syntactic complexity of a text while attempting to preserve (most of) its information content. It has recently emerged as an important research area, which holds promise for enhancing the text readability for the benefit of a broader audience as well as for increasing the performance of other applications. Our work focuses on syntactic complexity reduction and deals with the task of corpus-based acquisition of syntactic simplification rules for the French language. We show that the data-driven manual acquisition of simplification rules can be complemented by the semi-automatic detection of syntactic constructions requiring simplification. We provide the first comprehensive set of syntactic simplification rules for French, whose size is comparable to similar resources that exist for English and Brazilian Portuguese. Unlike these manually-built resources, our resource integrates larger lists of lexical cues signaling simplifiable constructions, that are useful for informing practical systems.