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DAARC
2007
Springer

Evaluating Hybrid Versus Data-Driven Coreference Resolution

9 years 8 months ago
Evaluating Hybrid Versus Data-Driven Coreference Resolution
Abstract. In this paper, we present a systematic evaluation of a hybrid approach of combined rule-based filtering and machine learning to Dutch coreference resolution. Through the application of a selection of linguistically-motivated negative and positive filters, which we apply in isolation and combined, we study the effect of these filters on precision and recall using two different learning techniques: memory-based learning and maximum entropy modeling. Our results show that by using the hybrid approach, we can reduce up to 92 % of the training material without performance loss. We also show that the filters improve the overall precision of the classifiers leading to higher F-scores on the test set.
Iris Hendrickx, Véronique Hoste, Walter Dae
Added 07 Jun 2010
Updated 07 Jun 2010
Type Conference
Year 2007
Where DAARC
Authors Iris Hendrickx, Véronique Hoste, Walter Daelemans
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