The Importance of Lexicalized Syntax Models for Natural Language Generation Tasks

Abstract

The parsing community has long recognized the importance of lexicalized models of syntax. By contrast, these models do not appear to have had an impact on the statistical NLG community. To prove their importance in NLG, we show that a lexicalized model of syntax improves the performance of a statistical text compression system, and show results that suggest it would also improve the performances of an MT application and a pure natural language generation system.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2002
Accession Number
ADA459361

Entities

People

  • Daniel Marcu
  • Hal Daynem Iii
  • Irene Langkilde-geary
  • Kenji Yamada
  • Kevin Knight

Organizations

  • University of Southern California

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Automated Text Summarization
  • California
  • Channel Models
  • Communities
  • Computational Linguistics
  • Demographic Cohorts
  • Error Analysis
  • Errors
  • Foreign Languages
  • Information Operations
  • Information Science
  • Language
  • Linguistics
  • Natural Languages
  • Social Sciences
  • Statistics

Fields of Study

  • Computer science

Readers

  • Computational Linguistics
  • Systems Analysis and Design