A first machine learning approach to pronominal anaphora resolution in Basque

Authors:
O. Arregi;K. Ceberio;A. Díaz De Illarraza;I. Goenaga;B. Sierra;A. Zelaia
Affiliations:
University of the Basque Country;University of the Basque Country;University of the Basque Country;University of the Basque Country;University of the Basque Country;University of the Basque Country
Venue:
IBERAMIA'10 Proceedings of the 12th Ibero-American conference on Advances in artificial intelligence
Year:
2010

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Abstract

In this paper we present the first machine learning approach to resolve the pronominal anaphora in Basque language. In this work we consider different classifiers in order to find the system that fits best to the characteristics of the language under examination. We do not restrict our study to the classifiers typically used for this task, we have considered others, such as Random Forest or VFI, in order to make a general comparison. We determine the feature vector obtained with our linguistic processing system and we analyze the contribution of different subsets of features, as well as the weight of each feature used in the task.