Coreference resolution is a key ingredient for the automatic interpretation of text. It has been studied mainly from a linguistic perspective, with an emphasis on establishing potential antecedents for pronouns. Practical applications, such as Information Extraction (IE), summarization and Question Answering (QA), require accurate identification of coreference relations between noun phrases in general. Computational systems for assigning such relations automatically, require the availability of a sufficient amount of annotated data for training and testing. For Dutch, annotated data is scarce and coreference resolution systems are lacking. In COREA, a robust system for assigning such relations automatically will be developed, and we will investigate the effect of making coreference relations explicit on the accuracy of systems for IE and QA.
Nederlandse TaalUnie (STEVIN)
This Demo is part of the Corea project and its purpose is to tag noun-phrase referents in a text.