Extraction d'entités dans des collections évolutives

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.