Towards a Balanced Named Entity Corpus for Dutch

AbstractThis paper introduces a new named entity corpus for Dutch. State-of-the-art named entity recognition systems require a substantial annotated corpus to be trained on. Such corpora exist for English, but not for Dutch. The STEVIN-funded SoNaR project aims to produce a diverse 500-million-word reference corpus of written Dutch, with four semantic annotation layers: named entities, coreference relations, semantic roles and spatiotemporal expressions. A 1-million-word subset will be manually corrected. Named entity annotation guidelines for Dutch were developed, adapted from the MUC and ACE guidelines. Adaptations include the annotation of products and events, the classification into subtypes, and the markup of metonymic usage. Inter-annotator agreement experiments were conducted to corroborate the reliability of the guidelines, which yielded satisfactory results (Kappa scores above 0.90). We are building a NER system, trained on the 1-million-word subcorpus, to automatically classify the remainder of the SoNaR corpus. To this end, experiments with various classification algorithms (MBL, SVM, CRF) and features have been carried out and evaluated.