We present a rule−based shallow− parser compiler, which allows to generate a robust shallow−parser for any language, even in the absence of training data, by resorting to a very limited number of rules which aim at identifying constituent boundaries. We contrast our approach to other approaches used for shallow−parsing (. finite−state and probabilistic methods). We present an evaluation of our tool for English (Penn Treebank) and for French (newspaper corpus "LeMonde") for several tasks (NP−chunking & "deeper" parsing) . .
