To understand texts written in natural language (LN), we use our knowledge
about the norms of the domain. Norms allow to infer more implicit information
from the text. This kind of information can, in general, be defeasible, but it
remains useful and acceptable while the text do not contradict it explicitly.
In this paper we describe a non-monotonic reasoning system based on the norms
of the car crash domain. The system infers the cause of an accident from its
textual description. The cause of an accident is seen as the most specific norm
which has been violated. The predicates and the rules of the system are
stratified: organized on layers in order to obtain an efficient reasoning