Abstract
In this paper, we describe our recent advances on a novel approach to Part-Of-Speech tagging based on neural networks. Multilayer perceptrons are used following corpus-based learning from contextual, lexical and morphological information. The Penn Treebank corpus has been used for the training and evaluation of the tagging system. The results show that the connectionist approach is feasible and comparable with other approaches.
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Zamora-Martínez, F., Castro-Bleda, M.J., España-Boquera, S., Tortajada-Velert, S. (2010). Adding Morphological Information to a Connectionist Part-Of-Speech Tagger. In: Meseguer, P., Mandow, L., Gasca, R.M. (eds) Current Topics in Artificial Intelligence. CAEPIA 2009. Lecture Notes in Computer Science(), vol 5988. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14264-2_20
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DOI: https://doi.org/10.1007/978-3-642-14264-2_20
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