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Dublin City University

Treebank-based automatic acquisition of wide coverage, deep linguistic resources for Japanese

Abstract

dc:description.abstract

The objective f this thesis is to design, implement and evaluate a methodology for the automatic acquisition of wide-coverage treebank-based deep linguistic resources fr Japanese, as part of the GramLab project which focuses on the automatic treebank-based induction of multilingual resources in the framework of Lexical-Functional Grammar (LFG). After introducing the basic framework of LFG in Chapter 2, I describe the core syntactic and morphological aspects of Japanese in Chapter 3: non-configurationality; the concept of "bunsetsu" r syntactic units and their dependency relationship represented in Directed Acyclic Graphs (DAGs); topicalisation by a particular particle; and frequent use of zero pronouns with or without over antecedents. Inflecting parts-of-speech and non-inflecting parts-of-speech of Japanese are also described with examples. In Chapter 4, I provide the linguistic representation of core grammatical features and functions of Japanese in the framework of LFG.I use Directed Acyclic Graphs (DAG) as a framework for the unified representation f surface syntactic, morphological and lexical information in an LFG f-structure. In Chapters 5 and 6, I describe the automatic annotation algorithm of LFG f-structure functional equations (i.e. labelled dependencies) to the Kyoto Text Corpus version 4.0 (KTC4) and the output of Kurohashi-Nagao Parser (KNP provide unlabelled dependencies only. The method presented in this dissertation also includes zero pronoun identification. Finally in Chapter 7 I evaluate the performance of the f-structure annotation algorithm with zero-pronoun identification for KTC4 against a manually-corrected Gold Standard of 500 sentences randomly chosen from KTC4. Using KTC4 treebank trees, currently my method achieves a pred-only dependency f-score of 94.72%. The parsing experiments using KNP output yield a pred-only dependency f-score of 82.38%.

Degree

thesis:*
Name dc:type.qualificationname
msc
Level dc:type.qualificationlevel
masters
Grantor dc:publisher.institution
Dublin City University
Year dc:date.issued
2010

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Oya, Masanori

Subjects

dc:subject × 1

Rights

Language dc:language
en

Identifiers

dc:identifier.*
Repository record dc:identifier.uri
https://doras.dcu.ie/15118/2/MasanoriOyaDeclaration.jpg
OAI identifier oai:identifier
oai:doras.dcu.ie:15118

Chain of custody

source
Harvested from
Dublin City University
Base URL
doras.dcu.ie/cgi/oai2
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Oya, Masanori. Treebank-based automatic acquisition of wide coverage, deep linguistic resources for Japanese. masters thesis, Dublin City University, 2010. https://doras.dcu.ie/15118/2/MasanoriOyaDeclaration.jpg