A semi-automatic tree annotating workbench for building a Korean treebank

Joon Ho Lim, So Young Park, Yong Jae Kwak, Hae Chang Rim

Research output: Chapter in Book/Report/Conference proceedingChapter

2 Citations (Scopus)

Abstract

In this paper, we propose a semi-automatic tree annotating workbench for building a Korean treebank. Generally, building a treebank requires an enormous effort by the annotator. In order to improve annotating efficiency, decrease the number of intervention required by the annotator, and help maintain consistent annotation in building a treebank, we have developed a semi-automatic tree annotating workbench consisting of following three stages: syntactic pattern extraction, syntactic pattern selection, and syntactic pattern application. The experiment was carried out with 27,966 tree tagged sentences as a training set and 3,108 sentences as a test set. As a result, the burden of manual annotation can be reduced by about 47% with the best selection of the feature set by using the proposed tree annotating workbench.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsAlexander Gelbukh
PublisherSpringer Verlag
Pages253-257
Number of pages5
ISBN (Print)3540210067, 9783540210061
DOIs
Publication statusPublished - 2004

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2945
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Lim, J. H., Park, S. Y., Kwak, Y. J., & Rim, H. C. (2004). A semi-automatic tree annotating workbench for building a Korean treebank. In A. Gelbukh (Ed.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 253-257). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2945). Springer Verlag. https://doi.org/10.1007/978-3-540-24630-5_31