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doi:10.22028/D291-24909
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Datei | Beschreibung | Größe | Format | |
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RR_91_04.pdf | 132,57 kB | Adobe PDF | Öffnen/Anzeigen |
Titel: | X2MORF : a morphological component based on augmented two-level morphology |
VerfasserIn: | Trost, Harald |
Sprache: | Englisch |
Erscheinungsjahr: | 1991 |
Quelle: | Kaiserslautern ; Saarbrücken : DFKI, 1991 |
Kontrollierte Schlagwörter: | Künstliche Intelligenz |
DDC-Sachgruppe: | 004 Informatik |
Dokumenttyp: | Forschungsbericht (Report zu Forschungsprojekten) |
Abstract: | In this paper I describe X2MORF, a language-independent morphological component for the recognition and generation of word forms based on a lexicon of morphs. The approach is an extension of two-level morphology. The extensions are motivated by linguistic examples 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 the 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 this 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. |
Link zu diesem Datensatz: | urn:nbn:de:bsz:291-scidok-36706 hdl:20.500.11880/24965 http://dx.doi.org/10.22028/D291-24909 |
Schriftenreihe: | Research report / Deutsches Forschungszentrum für Künstliche Intelligenz [ISSN 0946-008x] |
Band: | 91-04 |
Datum des Eintrags: | 28-Jun-2011 |
Fakultät: | SE - Sonstige Einrichtungen |
Fachrichtung: | SE - DFKI Deutsches Forschungszentrum für Künstliche Intelligenz |
Sammlung: | SciDok - Der Wissenschaftsserver der Universität des Saarlandes |
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