Compilation of constraint-based contextual rules for part-of-speech tagging into finite state transducers

Abstract

[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.