Large-scale knowledge-based machine translation requires significant amounts of lexical knowledge in order to map syntactic structures to conceptual structures. This paper presents a framework in which lexical knowledge is separated into different levels of representation, which are arranged in a hierarchical model based on principles of knowledge representation and lexical semantics. The proposed methodology is language-independent, and has been used to organize lexical knowledge for both English and Japanese
Building on the well-established premise that reliable machine translation requires a significant de...
Building on the well-established premise that reliable machine translation requires a significant de...
This paper describes a semi-automatic method for associating a Japanese lexicon with a semantic conc...
Large-scale knowledge-based machine translation requires ignificant amounts of lexical knowledge in ...
Machine translation should be semanticalty-accurate, linguistically-principled, user-interactive, an...
Machine translation should be semanticalty-accurate, linguistically-principled, user-interactive, an...
Machine translation should be semanticalty-accurate, linguistically-principled, user-interactive, an...
Machine translation should be semanticalty-accurate, linguistically-principled, user-interactive, an...
Machine translation should be semanticalty-accurate, linguisticallyprincipled, user-interactive, and...
Abstract. In knowledge-based machine translation (KBMT), the lexicon can be specified and acquired o...
Current approaches to generation for machine translation make use of direct-replacement templates, ...
The role of generic lexical resources as well as specialized terminology is crucial in the design of...
This report describes the organization and content of lexical information required for the task of m...
Knowledge-based machine translation can be viewed as the problem of extracting and representing the ...
Building on the well-established premise that reliable machine translation requires a significant de...
Building on the well-established premise that reliable machine translation requires a significant de...
Building on the well-established premise that reliable machine translation requires a significant de...
This paper describes a semi-automatic method for associating a Japanese lexicon with a semantic conc...
Large-scale knowledge-based machine translation requires ignificant amounts of lexical knowledge in ...
Machine translation should be semanticalty-accurate, linguistically-principled, user-interactive, an...
Machine translation should be semanticalty-accurate, linguistically-principled, user-interactive, an...
Machine translation should be semanticalty-accurate, linguistically-principled, user-interactive, an...
Machine translation should be semanticalty-accurate, linguistically-principled, user-interactive, an...
Machine translation should be semanticalty-accurate, linguisticallyprincipled, user-interactive, and...
Abstract. In knowledge-based machine translation (KBMT), the lexicon can be specified and acquired o...
Current approaches to generation for machine translation make use of direct-replacement templates, ...
The role of generic lexical resources as well as specialized terminology is crucial in the design of...
This report describes the organization and content of lexical information required for the task of m...
Knowledge-based machine translation can be viewed as the problem of extracting and representing the ...
Building on the well-established premise that reliable machine translation requires a significant de...
Building on the well-established premise that reliable machine translation requires a significant de...
Building on the well-established premise that reliable machine translation requires a significant de...
This paper describes a semi-automatic method for associating a Japanese lexicon with a semantic conc...