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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References
Ohta, T., Tateisi, Y., Kim, L., Mima, H., Tsujii, J.: The GENIA corpus: An annotated research abstract corpus in molecular biology domain. In: 2nd International Conference on Human Language Technology Research, San Diego, CA, USA, pp. 82–86 (2002)
Zhang, J., Shen, D., Zhou, G., Su, J., Tan, C.: Enhancing HMM-based biomedical named entity recognition by studying special phenomena. Journal of Biomedical Informatics 37, 411–422 (2004)
Alex, B., Haddow, B., Grover, C.: Recognising Nested Named Entities in Biomedical Text. In: BioNLP Workshop on Biological, translational, and clinical language processing, Prague, Czech Republic, pp. 65–72 (2007)
Arévalo, M., Civit, M., Martí, M.A.: MICE: A module for Named Entities Recognition and Classification. International Journal of Corpus Linguistics 9(1), 53–68 (2004)
Márquez, L., Martí, M.A., Taulé, M.: SemEval-2007 Task 09: Multilevel Semantic Annotation of Catalan and Spanish. In: 4th International Workshop on Semantic Evaluations, Prague, Czech Republic, pp. 42–47 (2007)
Márquez, L., Padró, L., Surdeanu, M., Villarejo, L.: UPC: Experiments with Joint Learning within SemEval Task 9. In: 4th International Workshop on Semantic Evaluations, Prague, Czech Republic, pp. 426–429 (2007)
Punyakanok, V., Roth, D.: The use of Classifiers in Sequential Inference. Advances in Neural Information Processing Systems 13, 995–1001 (2001)
McCallum, A., Freitag, D., Pereira, F.: Maximum Entropy Markov Models for Information Extraction and Segmentation. In: 17th International Conference on Machine Learning, Stanford, CA, USA, pp. 591–598 (2000)
Darroch, J., Ratcliff, D.: Generalized iterative scaling for log-linear models. The Annals of Mathematical Statistics 43, 1470–1480 (1972)
Martí, M.A., Taulé, M., Màrquez, L., Bertran, M.: CESS-ECE: A Multilingual and Multilevel Annotated Corpus (2007), http://www.lsi.upc.edu/~mbertran/cess-ece/publications
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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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