The authors describe a robust parsing strategy where partial parsing is seen not as a back-up strategy, but as the normal mode of operation of the parser. The goal is to extract from a lattice of word hypotheses the information content of an utterance using the minimum amount of linguistic knowledge. A system for accessing a train timetable in Italian has been implemented and tested on a test set of 600 utterances. The proposed approach to partial parsing represents a compromise between the need for accurate linguistic knowledge to avoid misunderstanding and the need to reduce the amount of linguistic knowledge to be used by the system, given its high development cost and the related reduction in efficiency and robustness. The approach makes it possible to increase robustness to spontaneous speech and to reduce the effect of limitations in the syntactic/semantic coverage of the grammar. The experiments show that the method has a good ability to extract correctly many concepts even when recognition problems do not make it possible to extract all of them. >