Please use this identifier to cite or link to this item: doi:10.22028/D291-24838
Title: Feature-based lexicons : an example and a comparison to DATR
Author(s): Nerbonne, John
Language: English
Year of Publication: 1992
OPUS Source: Kaiserslautern ; Saarbrücken : DFKI, 1992
SWD key words: Künstliche Intelligenz
Natürliche Sprache
DDC notations: 004 Computer science, internet
Publikation type: Report
Abstract: A FEATURE-BASED lexicon is especially sensible for natural language processing systems which are feature-based. Feature-based lexicons offer the advantages: (i) having a maximally transparent (empty) interface to feature-based grammars and processors; (ii) supplying exactly the EXPRESSIVE CAPABILITY exploited in these systems; and (iii) providing concise, transparent, and elegantspecification possibilities for various lexical relationships, including both inflection and derivation. The development of TYPED feature description languages allows the use of INHERITANCE in lexical description, and recent work explores the use of DEFAULT INHERITANCE as a means of easing lexical development. TDL is the implementation of a TYPE DESCRIPTION LANGUAGE based on HPSG feature logics. It is employed for both lexical and grammatical specification. As a lexical specification tool, it not only realizes these advantages, but it also separates a linguistic and a computational view of lexical contents and supplies a development environment for lexicon engineering. The most important competitor for feature-based lexical work is the very competent special purpose tool DATR, whose interface to feature-based systems is, however, inherently problematic. It is argued that feature-based systems (such as TDL) and DATR look compatible because of their common mathematical interpretation as graph description languages for directed graphs, but that this masks radically different modeling conventions for the graphs themselves. The development of TDL is continuing at the German Artificial Intelligence Center (Deutsches Forschungszentrum für Künstliche Intelligenz - DFKI) in the natural language understanding project DISCO.
Link to this record: urn:nbn:de:bsz:291-scidok-35907
Series name: Research report / Deutsches Forschungszentrum für Künstliche Intelligenz [ISSN 0946-008x]
Series volume: 92-04
Date of registration: 18-May-2011
Faculty: SE - Sonstige Einrichtungen
Department: SE - DFKI Deutsches Forschungszentrum für Künstliche Intelligenz
Collections:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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