Spanish Nested Named Entity Recognition Using a Syntax-Dependent Tree Traversal-Based Strategy

Authors:
Yunior Ramírez-Cruz;Aurora Pons-Porrata
Affiliations:
Center for Pattern Recognition and Data Mining, Universidad de Oriente, Santiago de Cuba, Cuba 90500;Center for Pattern Recognition and Data Mining, Universidad de Oriente, Santiago de Cuba, Cuba 90500
Venue:
MICAI '08 Proceedings of the 7th Mexican International Conference on Artificial Intelligence: Advances in Artificial Intelligence
Year:
2008

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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.