Learning Dutch Coreference Resolution

This paper presents a machine learning approach to the resolution of coreferential relations between nominal constituents in Dutch. It is the first significant automatic approach to the resolution of coreferential relations between nominal constituents for this language. The corpus-based strategy was enabled by the annotation of a substantial corpus (ca. 12,500 noun phrases) of Dutch news magazine text with coreferential links for pronominal, proper noun and common noun coreferences. Based on the hypothesis that different types of in- formation sources contribute to a correct resolution of different types of coreferential links, we propose a modular approach in which a separate module is trained per NP type.