Abstract
The problem of definite description reference is solved in this paper as a clustering task. We present a clustering algorithm based on semantics to classify definite description (anaphoric vs. non-anaphoric). Moreover, this clustering method helps to look for the correct antecedent using a resolution algorithm based on constrains and a preferences. The preference system uses a weight management to select the correct candidate belonged to the same cluster as the definite description. The EuroWordNet’s ontology provides the semantic class of definite description used to activate the correct cluster. Finally, we present some experiments related to this procedure. According to these experiments, a precision of 88.8% and a recall of 83.9% was obtained for definite description treatment and resolution.
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Muñoz, R., Palomar, M. (2001). Clustering Technique Based on Semantics for Definite Description Resolution. In: Matoušek, V., Mautner, P., Mouček, R., Taušer, K. (eds) Text, Speech and Dialogue. TSD 2001. Lecture Notes in Computer Science(), vol 2166. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44805-5_10
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DOI: https://doi.org/10.1007/3-540-44805-5_10
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