Approximating an Interlingua in a Principled Way

Abstract

We address the problem of constructing in a principled way an ontology of terms to be used in an interlingua for machine translation. Given our belief that a true language neutral ontology of terms can only be approached asymptotically, the construction method outlined involves a stepwise folding in of one language at a time. This is effected in three steps: first building for each language taxonomy of the linguistic generalizations required to analyze and generate that language, then organizing the domain entities in terms of that taxonomy, and finally merging the result with the existing interlingua ontology in a well-defined way. This methodology is based not on intuitive grounds about what is and is not 'true' about the world, which is a question of language- independence, but instead on practical concerns, namely what information the analysis and generation programs require in order to perform their tasks, a question of language-neutrality. After each merging is complete, the resulting taxonomy contains, declaratively and explicitly represented, those distinctions required to control the analysis and generation of the linguistic phenomena. The paper is based on current work of the PANGLOSS MT project. Machine translation, Interlingua, Semantic ontology, Computational linguistics.

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Document Details

Document Type
Technical Report
Publication Date
Feb 01, 1992
Accession Number
ADA269723

Entities

People

  • Eduard H. Hovy
  • Sergie Nirenburg

Organizations

  • University of Southern California

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Acquisition
  • Analyzers
  • Classification
  • Computational Linguistics
  • Grammars
  • Information Science
  • Language
  • Linguistics
  • Machine Translation
  • Natural Language Processing
  • Natural Languages
  • Ontologies
  • Psychology
  • Reasoning
  • Semantics
  • Taxonomy
  • Universities

Readers

  • Artificial Intelligence
  • Computational Linguistics
  • Regression Analysis.

Technology Areas

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