Normalizing Syntactic Structure Using Part-of-Speech Tags and Binary Rules(<Special Issue> Development of Advanced Computer Systems)
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概要
- 論文の詳細を見る
We propose a normalization scheme of syntactic structures using a binary phrase structure grammar with composite labels. The normalization adopts binary rules so that the dependency between two sub-trees can be represented in the label of the tree. The label of a tree is composed of two attributes, each of which is extracted from each sub-tree, so that it can represent the compositional information of the tree. The composite label is generated from part-of-speech tags using an automatic labelling algorithm. Since the proposed normalization scheme is binary and uses only part-of-speech information, it can readily be used to compare the results of different syntactic analyses independently of their syntactic description and can be applied to other languages as well. It can also be used for syntactic analysis, which performs higher than the previous syntactic description for Korean corpus. We implement a tool that transforms a syntactic description into normalized one based on this proposed scheme. It can help construct a unified syntactic corpus and extract syntactic information from various types of syntactic corpus in a uniform way.
- 社団法人電子情報通信学会の論文
- 2003-10-01
著者
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CHOI Key-Sun
Dept. of Computer Science, KAIST
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Choi Key-sun
Dept. Of Computer Science Kaist
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Choi Key-sun
Dept. Of Eecs Kaist
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KIM Seongyong
Dept. of EECS, KAIST
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LEE Kong-Joo
Dept. of CSE, Ewha Womans Univ.
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Lee Kong-joo
Dept. Of Cse Ewha Womans Univ.
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Kim Seongyong
Dept. Of Eecs Kaist
関連論文
- An Alignment Model for Extracting English-Korean Translations of Term Constituents(Natural Language Processing)
- Normalizing Syntactic Structure Using Part-of-Speech Tags and Binary Rules( Development of Advanced Computer Systems)
- Extracting Partial Parsing Rules from Tree-Annotated Corpus : Toward Deterministic Global Parsing(Natural Language Processing)
- Improving Automatic English Writing Assessment Using Regression Trees and Error-Weighting