Machine Translation

, Volume 17, Issue 2, pp 99–137

Construction of a Chinese–English Verb Lexicon for Machine Translation and Embedded Multilingual Applications

Authors

  • Bonnie Jean Dorr
    • University of Maryland Institute for Advanced Computer Studies
  • Gina-Anne Levow
    • University of Maryland Institute for Advanced Computer Studies
  • Dekang Lin
    • University of Alberta
Article

DOI: 10.1023/B:COAT.0000010116.83274.c3

Cite this article as:
Dorr, B.J., Levow, G. & Lin, D. Machine Translation (2002) 17: 99. doi:10.1023/B:COAT.0000010116.83274.c3

Abstract

This paper addresses the problem of automatic acquisition of lexical knowledge for rapid construction of engines for machine translation and embedded multilingual applications. We describe new techniques for large-scale construction of a Chinese–English verb lexicon and we evaluate the coverage and effectiveness of the resulting lexicon. Leveraging off an existing Chinese conceptual database called How Net and a large, semantically rich English verb database, we use thematic-role information to create links between Chinese concepts and English classes. We apply the metrics of recall and precision to evaluate the coverage and effectiveness of the linguistic resources. The results of this work indicate that: (a) we are able to obtain reliable Chinese–English entries both with and without pre-existing semantic links between the two languages; (b) if we have pre-existing semantic links, we are able to produce a more robust lexical resource by merging these with our semantically rich English database; (c) in our comparisons with manual lexicon creation, our automatic techniques were shown to achieve 62% precision, compared to a much lower precision of 10% for arbitrary assignment of semantic links.

resource alignmentChinese–English lexiconsthematic roleslexical acquisition

Copyright information

© Kluwer Academic Publishers 2002