Abstract
With the aim of removing the residuary errors made by pure stochastic disambiguation models, we put forward a hybrid system in which linguist users introduce high level contextual rules to be applied in combination with a tagger based on a Hidden Markov Model. The design of these rules is inspired in the Constraint Grammars formalism. In the present work, we review this formalism in order to propose a more intuitive syntax and semantics for rules, and we develop a strategy to compile the rules under the form of Finite State Transducers, thus guaranteeing an efficient execution framework.
This work has been partially supported by the Spanish Government (under projects TIC2000-0370-C02-01 and HP2001-0044), and by the Galician Government (under project PGIDT01PXI10506PN).
Galena means Generation of Natural Language Analyzers and Corga means Reference Corpus of Current Galician. See http://coleweb.dc.fi.udc.es for more information on both projects.
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Graña, J., Andrade, G., Vilares, J. (2003). Compilation of Constraint-Based Contextual Rules for Part-of-Speech Tagging into Finite State Transducers. In: Champarnaud, JM., Maurel, D. (eds) Implementation and Application of Automata. CIAA 2002. Lecture Notes in Computer Science, vol 2608. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44977-9_12
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DOI: https://doi.org/10.1007/3-540-44977-9_12
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