  This paper describes how robust parsing techniques can be fruitful applied
for building a query generation module which is part of a pipelined NLP
architecture aimed at process natural language queries in a restricted domain.
We want to show that semantic robustness represents a key issue in those NLP
systems where it is more likely to have partial and ill-formed utterances due
to various factors (e.g. noisy environments, low quality of speech recognition
modules, etc...) and where it is necessary to succeed, even if partially, in
extracting some meaningful information.
