Machine Translation Using Abductive Inference

Abstract

Machine Translation and World Knowledge. Many existing approaches to machine translation take for granted that the information presented in the output is found somewhere in the input, and, moreover, that such information should be expressed at a single representational level, say, in terms of the parse trees or of semantic assertions. Languages, however, not only express the equivalent information by drastically different linguistic means, but also often disagree in what distinctions should be expressed linguistically at all. For example, in translating from Japanese to English, it is often necessary to suppy determiners for noun phrases, and this in general cannot be done without deep understanding of the source text. Similarly, intranslating from English to Japanese, politeness considerations, which in English are implicit in the social situation and explicit in very diffuse ways in, for example, the heavy use of hypotheticals, must be realized grammatically in Japanese. Machine translation therefore requires that the appropriate inferences be drawn and that the text be interpreted to some depth.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1990
Accession Number
ADA259458

Entities

People

  • Jerry R. Hobbs
  • Megumi Kameyama

Organizations

  • SRI International

Tags

DTIC Thesaurus Topics

  • Applied Computer Science
  • Artificial Intelligence
  • Artificial Intelligence Software
  • Computational Linguistics
  • Computational Science
  • Demographic Cohorts
  • Grammars
  • Language
  • Linguistics
  • Machine Translation
  • Natural Languages
  • New York
  • Particles
  • Semantics
  • Three Dimensional
  • Translations

Readers

  • Computational Linguistics

Technology Areas

  • AI & ML
  • AI & ML - Machine Translation
  • AI & ML - Neural Networks