Clique-based clustering for improving named entity recognition systems

Julien Ah-Pine (1) , Guillaume Jacquet

1 Xerox Research Centre Europe [Meylan]

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 clique-based clustering system allows to improve different NER systems.

Domaines: Informatique et langage [cs.CL]; Apprentissage [cs.LG]

Julien Ah-Pine, Guillaume Jacquet. Clique-based clustering for improving named entity recognition systems. 12th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2009), Mar 2009, Athènes, Greece. pp.51-59, ⟨10.3115/1609067.1609072⟩. ⟨hal-01504505⟩