Please use this identifier to cite or link to this item:
doi:10.22028/D291-25130
Title: | Knowledge-based disambiguation for machine translation |
Author(s): | Quantz, J. Joachim Schmitz, Birte |
Language: | English |
Year of Publication: | 1994 |
OPUS Source: | Saarbrücken, 1994 |
SWD key words: | Künstliche Intelligenz |
DDC notations: | 004 Computer science, internet |
Publikation type: | Report |
Abstract: | The resolution of ambiguities is one of the central problems for Machine Translation. In this paper we propose a knowledge-based approach to disambiguation which uses Description Logics (DL) as representation formalism. We present the process of anaphora resolution implemented in the Machine Translation system FAST and show how the DL system BACK is used to support disambiguation. The disambiguation strategy uses factors representing syntactic, semantic, and conceptual constraints with different weights to choose the most adequate antecedent candidate. We show how these factors can be declaratively represented as defaults in BACK. Disambiguation is then achieved by determining the interpretation that yields a qualitatively minimal number of exceptions to the defaults, and can thus be formalized as exception minimization. |
Link to this record: | urn:nbn:de:bsz:291-scidok-40828 hdl:20.500.11880/25186 http://dx.doi.org/10.22028/D291-25130 |
Series name: | Vm-Report / Verbmobil, Verbundvorhaben, [Deutsches Forschungszentrum für Künstliche Intelligenz] |
Series volume: | 44 |
Date of registration: | 3-Aug-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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File | Description | Size | Format | |
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report_44_94.pdf | 131,39 kB | Adobe PDF | View/Open |
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