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Automatic semantic role labeling in a Dutch corpus

We present an approach to automatic semantic role labeling (SRL) carried out in the context 
of the D-coi project. Although there has been an increasing interest in automatic SRL in 
recent years, previous research has focused mainly on English. Adapting earlier research to 
the Dutch situation poses an interesting challenge especially because there is no semantically 
annotated Dutch corpus available that can be used as training data. Our automatic SRL 
approach consists of three steps: bootstrapping from an unannotated corpus with a rulebased 
tagger developed for this purpose, manual correction and training a machine learning 
system on the manually corrected data. The input data for our SRL approach consists of 
Dutch sentences from the D-COI corpus, syntactically annotated by the Dutch dependency 
parser Alpino.