Rapid Parser Development: A Machine Learning Approach for Korean

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Rapid Parser Development: A Machine Learning Approach for Korean (2000)

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by Ulf Hermjakob

Venue:	In Proceedings of the North American chapter of the Association for Computational Linguistics (NAACL2000). http://www.isi.edu/~ulf/papers/kor_naacl00.ps.gz
Citations:	9 - 6 self

BibTeX

@INPROCEEDINGS{Hermjakob00rapidparser,
    author = {Ulf Hermjakob},
    title = {Rapid Parser Development: A Machine Learning Approach for Korean},
    booktitle = {In Proceedings of the North American chapter of the Association for Computational Linguistics (NAACL2000). http://www.isi.edu/~ulf/papers/kor_naacl00.ps.gz},
    year = {2000},
    pages = {118--123}
}

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Abstract

This paper demonstrates that machine learning is a suitable approach for rapid parser development. From 1000 newly treebanked Korean sentences we generate a deterministic shift-reduce parser. The quality of the treebank, particularly crucial given its small size, is supported by a consistency checker.

Keyphrases

rapid parser development machine learning approach suitable approach consistency checker machine learning deterministic shift-reduce parser korean sentence small size

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