Please use this identifier to cite or link to this item:
doi:10.22028/D291-25232
Title: | Incremental syntactic generation of natural language with tree adjoining grammars |
Author(s): | Schauder, Anne |
Language: | English |
Year of Publication: | 1992 |
OPUS Source: | Kaiserslautern ; Saarbrücken : DFKI, 1992 |
SWD key words: | Künstliche Intelligenz |
Free key words: | Artificial Intelligence |
DDC notations: | 004 Computer science, internet |
Publikation type: | Report |
Abstract: | This document combines the basic ideas of my master´s thesis - which has been developped within the WIP project - with new results from my work as a member of WIP, as far as they concern the integration and further development of the implemented system. ISGT (in German 'Inkrementeller Syntaktischer Generierer natürlicher Sprache mit TAGs´) is a syntactic component for a text generation system and is based on Tree Adjoining Grammars. It is lexically guided and consists of two levels of syntactic processing: A component that computes the hierarchical structure of the sentence under construction (hierarchical level) and a component that computes the word position and utters the sentence (positional level). The central aim of this work has been to design a syntactic generator that computes sentences in an incremental fashion. The realization of the incremental syntactic generator has been supported by a distributed parallel model that is used to speed up the computation of single parts of the sentence. |
Link to this record: | urn:nbn:de:bsz:291-scidok-50618 hdl:20.500.11880/25288 http://dx.doi.org/10.22028/D291-25232 |
Series name: | Document / Deutsches Forschungszentrum für Künstliche Intelligenz : D [ISSN 0946-0098] |
Series volume: | 92-21 |
Date of registration: | 7-Mar-2013 |
Faculty: | SE - Sonstige Einrichtungen |
Department: | SE - DFKI Deutsches Forschungszentrum für Künstliche Intelligenz |
Collections: | SciDok - Der Wissenschaftsserver der Universität des Saarlandes |
Files for this record:
File | Description | Size | Format | |
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D_92_21_.pdf | 33,34 MB | Adobe PDF | View/Open |
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