Finite-State Technology as a Programming Environment

Abstract

Finite-state technology is considered the preferred model for representing the phonology and morphology of natural languages. The attractiveness of this technology for natural language processing stems from four sources: modularity of the design, due to the closure properties of regular languages and relations; the compact representation that is achieved through minimization; efficiency, which is a result of linear recognition time with finite-state devices; and reversibility, resulting from the declarative nature of such devices.However, when wide-coverage grammars are considered, finite-state technology does not scale up well, and the benefits of this technology can be overshadowed by the limitations it imposes as a programming environment for language processing. This paper focuses on several aspects of large-scale grammar development. Using a real-world benchmark, we compare a finite-state implementation with an equivalent Java program with respect to ease of development, modularity, maintainability of the code and space and time efficiency. We identify two main problems, abstraction and incremental development, which are currently not addressed sufficiently well by finite-state technology, and which we believe should be the focus of future research and development.KeywordsNatural Language ProcessingMachine TranslationRegular ExpressionRegular LanguageLinguistic KnowledgeThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.