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Current approaches to generation for machine translation make use of direct-replacement templates, large grammars, and knowledge-based inferencing techniques. Not only are rules language-specific, but they are too simplistic to handle sentences that exhibit more complex phenomena. Furthermore, these systems are not easily extendable to other languages because the rules that map the internal representation to the surface form are entirely dependent on both the domain of the system and the language being generated. Finally an adequate interlingual representation has not yet been discovered; thus, knowledge-based inferencing is necessary and syntactic cross-linguistic generalization cannot be exploited. This report introduces a plan for the development of a theoretically based computational scheme of natural language generation for a translation system. The emphasis of the project is the mapping from the lexical conceptual structure of sentences to an underlying or base syntactic structure called deep structure. This approach tackles the problems of thematic and structural divergence, i.e., it allows generation of target language sentences that are not thematically or structurally equivalent to their conceptually equivalent source language counterparts. Two other more secondary tasks, construction of a dictionary and mapping from deep structure to surface structure, will also be discussed. The generator operates on a constrained grammatical theory rather than on a set of surface level transformations. (kr).
To determine the correct lexical items and syntactical realization associated with the surface form in such cases, the underlying lexical-semantic forms are systematically mapped to the target-language syntactic structures. The model described constitutes a lexical-semantic extention to UNITRAN [Dorr, 1987], a syntactic-based translation system that is bidirectional between Spanish and English."
This book describes a novel, cross-linguistic approach to machine translation that solves certain classes of syntactic and lexical divergences by means of a lexical conceptual structure that can be composed and decomposed in language-specific ways. This approach allows the translator to operate uniformly across many languages, while still accounting for knowledge that is specific to each language.
This book aims to inform scholars working in the domain of natural language generation (man-machine interface, automatic translation, text generation) about the most recent advances in the field whether in the domain of grammar theories or discourse planning, ie how to structure the message in such a way that the reader can easily follow the writer's train of thought. It is in particular in this domain, discourse planning, that significant advances has been achieved during the last five years.
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