Abstract
The Anaphora Resolution task of Evalita 2011 was intended to measure the ability of participating systems to recognize mentions of the same real-world entity within a given document. The UNIPI system is based on the analysis of dependency parse trees and on similarity clustering. Mention detection relies on parse trees obtained by re-parsing texts with DeSR, and on ad-hoc heuristics to deal with specific cases, when mentions boundaries do not correspond to sub-trees. A binary classifier, based on Maximum Entropy, is used to decide whether there is a coreference relationship between each pair of mentions detected in the previous phase. Clustering of entities is performed by a greedy clustering algorithm.
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Attardi, G., Dei Rossi, S., Simi, M. (2013). UNIPI Participation in the Evalita 2011 Anaphora Resolution Task. In: Magnini, B., Cutugno, F., Falcone, M., Pianta, E. (eds) Evaluation of Natural Language and Speech Tools for Italian. EVALITA 2012. Lecture Notes in Computer Science(), vol 7689. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35828-9_17
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DOI: https://doi.org/10.1007/978-3-642-35828-9_17
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