  This paper reports on the "Learning Computational Grammars" (LCG) project, a
postdoc network devoted to studying the application of machine learning
techniques to grammars suitable for computational use. We were interested in a
more systematic survey to understand the relevance of many factors to the
success of learning, esp. the availability of annotated data, the kind of
dependencies in the data, and the availability of knowledge bases (grammars).
We focused on syntax, esp. noun phrase (NP) syntax.
