Abstract
This paper proposes an approach to reduce the stochastic parsing time with stochastic context-free grammars. The basic idea consists of storing a set of precomputed problems. These precomputed problems are obtained off line from a training corpus or they are computed on line from a test corpus. In this work, experiments with the UPenn Treebank are reported in order to show the performance of both alternatives.
This work has been partially supported by the Spanish MCyT under contract (TIC2002/04103-C03-03) and by Agencia Valenciana de Ciencia y Tecnología under contract GRUPOS03/031.
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Sánchez, J.A., Benedí, J.M. (2005). Time Reduction of Stochastic Parsing with Stochastic Context-Free Grammars. In: Marques, J.S., Pérez de la Blanca, N., Pina, P. (eds) Pattern Recognition and Image Analysis. IbPRIA 2005. Lecture Notes in Computer Science, vol 3523. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11492542_21
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DOI: https://doi.org/10.1007/11492542_21
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