Clique-Based Clustering for Improving Named Entity Recognition Systems

We propose a system which builds, in a semi-supervised manner, a resource that aims at helping a NER system to annotate corpus-specific named entities. This system is based on a distributional approach which uses syntactic dependencies for measuring similarities between named entities. The specificity of the presented method however, is to combine a clique-based approach and a clustering technique that amounts to a soft clustering method. Our experiments show that the resource constructed by using this cliquebased clustering system allows to improve different NER systems.