  The goal of our work is to use a set of reports and extract named entities,
in our case the names of Industrial or Academic partners. Starting with an
initial list of entities, we use a first set of documents to identify syntactic
patterns that are then validated in a supervised learning phase on a set of
annotated documents. The complete collection is then explored. This approach is
similar to the ones used in data extraction from semi-structured documents
(wrappers) and do not need any linguistic resources neither a large set for
training. As our collection of documents would evolve over years, we hope that
the performance of the extraction would improve with the increased size of the
training set.
