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An Extension of LangLAB for Japanese Morphological Analysis
An Extension of LangLAB for Japanese Morphological Analysis
Tomoyosi Akiba, Takenobu Tokunaga, Hozumi Tanaka
Department of Computer Science
Tokyo Institute of Technology
2-12-1
^
Ookayama Meguro Tokyo 152 Japan
fakiba,take,tanakag@cs.titech.ac.jp
Abstract
LangLAB is a natural language analysing system which adopts a bottom-up, depth- rst
parsing strategy. LangLAB has useful features to analyse English text. This paper describes
an extension of the LangLAB system in order to analyse Japanese. In particular, a morpho-
logical analysis program of Japanese is proposed. The representation form of grammar rules
(DCG) and dictionary description (DRF) are also extended to handle the morphological
information.
1 Introduction
LangLAB [5] provides the users a facility to build a natural language analysis system. The users
only have to prepare grammar and a dictionary. Some of the signi cant features of LangLAB
are listed below.
Bottom-up depth- rst parsing strategy is adopted. This allows left-recursive grammar
rules.
The grammar description form XGS provides a device to describe gapping phenomena
which typically appear in relative clauses of English.
A TRIE-structured dictionary is adopted to enable ecient and
exible reference to the
dictionary. Easy way of handling idioms is also possible.
Morphological analysis and syntactic analysis are performed at the same time. Semantic
analysis can also be performed by using augmentation of DCG in which we can write any
Prolog programs.
LangLAB runs on any Prolog which has the same syntax as that of DEC-10 Prolog. The
current version runs on C-Prolog, Quintus-Prolog and SICStus-Prolog.
This paper describes an extension of LangLAB system in order to analyse Japanese. In
particular, a morphological analysis program of Japanese is proposed. Morphological analysis
of Japanese is very di erent from that of English, because no spaces are placed between words.
The analysis includes segmentation of words and handling in
ections.
Th
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