  This paper discusses SYNTAGMA, a rule based NLP system addressing the tricky
issues of syntactic ambiguity reduction and word sense disambiguation as well
as providing innovative and original solutions for constituent generation and
constraints management. To provide an insight into how it operates, the
system's general architecture and components, as well as its lexical, syntactic
and semantic resources are described. After that, the paper addresses the
mechanism that performs selective parsing through an interaction between
syntactic and semantic information, leading the parser to a coherent and
accurate interpretation of the input text.
