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. © Springer-Verlag Berlin Heidelberg 2003.
CITATION STYLE
Graña, J., Andrade, G., & Vilares, J. (2003). Compilation of constraint-based contextual rules for part-of-speech tagging into finite state transducers. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2608, 128–137. https://doi.org/10.1007/3-540-44977-9_12
Mendeley helps you to discover research relevant for your work.