Large-scale knowledge-based machine translation requires significant amounts of lexical knowledge in order to map syntactic structures to conceptual.
This paper presents a framework in which lexical knowledge is separated into different levels of representation, which are arranged in a hierarchical model ...
Large-scale knowledge-based machine translation requires significant amounts of lexical knowledge in order to map syntactic structures to conceptual structures.
A framework in which lexical knowledge is separated into different levels of representation, which are arranged in a hierarchical model based on principles ...
Aug 6, 2021 · Teruko Mitamura, Eric Nyberg: Hierarchical Lexical Structure And Interpretive Mapping In Machine Translation. COLING 1992: 1254-1258.
TL;DR: The main contribution of this thesis is to give a full-fledged model of interpretive mapping for knowledge-based machine translation, and to offer ...
Hierarchical Lexical Structure And Interpretive Mapping In Machine Translation. Resource URI: https://dblp.l3s.de/d2r/resource/publications/conf/coling ...
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Feb 24, 2004 · "Hierarchical Lexical Structure and Interpretive Mapping in Machine Translation" Proceedings of COLING-92. Nyberg and Mitamura (1992) ...
The Hierarchical Organization of Predicate Frames for Interpretive Mapping in Natural Language Processing. Ph.D. thesis, University of Pittsburgh. Mitamura, T.
Jul 16, 2002 · "Hierarchical Lexical Structure and Interpretive Mapping in Machine Translation" Proceedings of COLING-92. Nyberg and Mitamura (1992) ...
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