Earticle

초록

영어

Automatically acquiring semantic verb classes from corpora is a challenging task, especially with no existing treebank. Building a high-performing parser for a language is still crucially depends on the existence of large, in-domain texts as training data. While previous work has focused primarily on major languages, how to extend these results to other languages is the way to avoid working start from scratch. In general, a large monolingual corpus in a resource-rich source language labeled with lexico-syntactic information, and a very limited bilingual corpus are available. This paper addresses the problem of verb classification automatically in Tibetan using bilingual lexicon and translation information.

목차

Abstract
 1. Introduction
 2. Related Work
 3. Corpus Used
  3.1 Data Resources
  3.2 Verb Classes in Tibetan Language
 4. Verb Classification Method
  4.1 Candidate Selection by Translation Information
  4.2 Verb Classification by Translation Information
 5. Experiments
 6.. Conclusion and Future Work
 Acknowledgements
 References

키워드

저자

• Lirong Qiu [ School of Information Engineering, Minzu University of China, Beijing, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Multimedia and Ubiquitous Engineering

• 간기

  월간

• pISSN

  1975-0080

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605