Departamento de
Traducción e Interpretación


Tema:   Automática. Ambigüedad. Problema.
Autor:   Specia, Lucia
Año:   2007
Título:   Uma abordagem híbrida relacional para a desambiguação lexical de sentido na tradução automática [A hybrid relational approach for word sense disambiguation in machine translation]
Lugar:   São Paulo
Editorial/Revista:   Universidade de São Paulo (USP)
Páginas:   266
Idioma:   Portugués.
Tipo:   Tesis.
ISBN/ISSN/DOI:   DOI: 10.11606/T.55.2007.tde-05122007-205308
Disponibilidad:   Acceso abierto.
Resumen:   Crosslingual communication has become a very imperative task in the current scenario with the increasing amount of information dissemination in several languages. In this context, machine translation systems, which can facilitate such communication by providing automatic translations, are of great importance. Although research in Machine Translation dates back to the 1950's, the area still has many problems. One of the main problems is that of lexical ambiguity, that is, the need for lexical choice when translating a source language word that has several translation options in the target language. This problem is even more complex when only sense variations are found in the translation options, a problem named "sense ambiguity". Several approaches have been proposed for word sense disambiguation, but they are in general monolingual (for English) and application-independent. Moreover, they have limitations regarding the types of knowledge sources that can be exploited. Particularly, there is no significant research aiming to word sense disambiguation involving Portuguese. The goal of this PhD work is the proposal and development of a novel approach for word sense disambiguation which is specifically designed for machine translation, follows a hybrid methodology (knowledge and corpus-based), and employs a relational formalism to represent various kinds of knowledge sources and disambiguation examples, by using Inductive Logic Programming. Several experiments have shown that the proposed approach overcomes alternative approaches in multilingual disambiguation and achieves higher or comparable results to the state of the art in monolingual disambiguation. Additionally, the approach has shown to effectively assist lexical choice in a statistical machine translation system. [Source: Author]
Agradecimientos:   Record supplied by Katia Aily Franco de Camargo – (Universidade Federal do Rio Grande do Norte – UFRN)
2001-2019 Universidad de Alicante DOI: 10.14198/bitra
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