We present a robust full-featured architecture to preprocess text before parsing. This architecture, called SxPipe, converts raw noisy corpora into word lattices, one by sentence, that can be used as input by a parser. It includes sequentially named-entity recognition, tokenization and sentence boundaries detection, lexicon-aware named-entity recognition, spelling correction, and non-deterministic multi-words processing, re-accentuation and un-/re-capitalization. Though our system currently deals with the French language, almost all components are in fact language-independent, and the others can be straightforwardly adapted to virtually any inflectional language. The output is a sequence of word lattices, all words being present in the lexicon. It has been applied on a large scale during a French parsing evaluation campaign and during experiments of large corpora parsing, showing both good efficiency and very satisfying precision and recall.