PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Evaluating hybrid versus data-driven coreference resolution
Iris Hendrickx, Veronique Hoste and Walter Daelemans
In: Anaphora: Analysis, Algorithms and Applications Lecture Notes in Computer Science (4410). (2007) Springer Verlag , Berlin , pp. 137-150.

Abstract

In this paper, we present a systematic evaluation of a hy- brid 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 learn- ing and maximum entropy modeling. Our results show that by using the hybrid approach, we can reduce up to 92 % of the training material with- out performance loss. We also show that the filters improve the overall precision of the classifiers leading to higher F-scores on the test set.

EPrint Type:Book Section
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Natural Language Processing
ID Code:3896
Deposited By:Walter Daelemans
Deposited On:25 February 2008