Hybrid Natural Language Generation from Lexical Conceptual Structures

Nizar Habash, Bonnie Dorr, David Traum

Research output: Contribution to journalReview articlepeer-review


This paper describes Lexogen, a system for generating natural-language sentences from Lexical Conceptual Structure, an interlingual representation. The system has been developed as part of a Chinese-English Machine Translation (MT) system; however, it is designed to be used for many other MT language pairs and natural language applications. The contributions of this work include: (1) development of a large-scale Hybrid Natural Language Generation system with language-independent components; (2) enhancements to an interlingual representation and associated algorithm for generation from ambiguous input; (3) development of an efficient reusable language-independent linearization module with a grammar description language that can be used with other systems; (4) improvements to an earlier algorithm for hierarchically mapping thematic roles to surface positions; and (5) development of a diagnostic tool for lexicon coverage and correctness and use of the tool for verification of English, Spanish, and Chinese lexicons. An evaluation of Chinese-English translation quality shows comparable performance with a commercial translation system. The generation system can also be extended to other languages and this is demonstrated and evaluated for Spanish.

Original languageEnglish (US)
Pages (from-to)81-128
Number of pages48
JournalMachine Translation
Issue number2
StatePublished - 2003


  • Hybrid Natural Language Generation
  • Interlingua
  • Lexical Conceptual Structure
  • Multilingual Natural Language Generation

ASJC Scopus subject areas

  • Software
  • Language and Linguistics
  • Linguistics and Language
  • Artificial Intelligence


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