Abstract
In this paper, we address the problem of nested Named Entity Recognition (NER) for Spanish. Phrase syntactic structure is exploited to generate a tree representation for the set of phrases that are candidate to be named entities. The classification of all candidate phrases is treated as a single problem, for which a globally optimal solution is approximated using a strategy based on the postorder traversal of that representation. Experimental results, obtained in the framework of SemEval 2007 Task 9 NER subtask, demonstrate the validity of our approach.
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Ramírez-Cruz, Y., Pons-Porrata, A. (2008). Spanish Nested Named Entity Recognition Using a Syntax-Dependent Tree Traversal-Based Strategy. In: Gelbukh, A., Morales, E.F. (eds) MICAI 2008: Advances in Artificial Intelligence. MICAI 2008. Lecture Notes in Computer Science(), vol 5317. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88636-5_13
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DOI: https://doi.org/10.1007/978-3-540-88636-5_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-88635-8
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