Information-based syntax and semantics: Vol. 1: fundamentals
Information-based syntax and semantics: Vol. 1: fundamentals
Semantic-head-driven generation
Computational Linguistics
Überlegungen zu einer Two-level Morphologie für das Deutsche
4. Österreichische Artificial-Intelligence-Tagung, Wiener Workshop Wissensbasierte Sprachverarbeitung
Constraint propagation in Kimmo systems
ACL '86 Proceedings of the 24th annual meeting on Association for Computational Linguistics
A morphological recognizer with syntactic and phonological rules
COLING '86 Proceedings of the 11th coference on Computational linguistics
Morphology with two-level rules and negative rule features
COLING '88 Proceedings of the 12th conference on Computational linguistics - Volume 1
Unification and transduction in computational phonology
COLING '88 Proceedings of the 12th conference on Computational linguistics - Volume 1
A finite state approach to German verb morphology
COLING '88 Proceedings of the 12th conference on Computational linguistics - Volume 1
The applicaton of two-level morphology to non-concatenative German morphology
COLING '90 Proceedings of the 13th conference on Computational linguistics - Volume 2
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X2MORF is a language independent morphological component for the recognition and generation of word forms based on a lexicon of morphs. The approach is based on two-level morphology. Extensions are motivated by linguistic data which call into question an underlying assumption of standard two-level morphology, namely the independence of morphophonology and morphology as exemplified by two-level rules and continuation classes. Accordingly, I propose a model which allows for interaction between these two parts. Instead of using continuation classes, word formation is described in a feature-based unification grammar. Two-level rules are provided with a morphological context in the form of feature structures. Information contained in the lexicon and the word formation grammar guides the application of two-level rules by matching the morphological context against the morphs. I present an efficient implementation of that model where rules are compiled into automata (as in the standard model) and where processing of the feature-based grammar is enhanced using an automaton derived from that grammar as a filter.