Automatic sentence Parsing for Amharic Text an experiment using probabilistic Context free grammar
No Thumbnail Available
Date
2002-07
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Addis Ababa University
Abstract
Natural Language processing, as a field of scientific inquiry, plays an important role
in increasing computers capability to understand natural languages, the language by
which most human knowledge is recorded. Works in the area of Natural Language
Processing try to design and implement computer programs that can understand
natural language and act appropriately on the information contained in the text or
utterance. Enabling computers to understand natural language involves extraction of
meaning from natural language sentences. And one of the steps in this process is
sentence parsing.
Sentence parsing, which is also called syntactic parsing, is the process of identifying
how words can be put together to form correct sentences and determining what
structural role each word plays in the sentence and what phrases are subparts of
what other phrases. A sentence parser outputs a parse structure that could be used
as a component in many applications including semantic analysis, machine
translation, information storage and retrieval of textual data etc.
Today, parsers of different kinds (e.g. probabilistic, rule based) have been developed
for languages, which have relatively wider use nationally and/or internationally (e .g.
English, German, Chinese, etc). The same story is not true for Amharic, the working
language of the Federal Government of Ethiopia, and one of the major languages of
Ethiopia (Bender et ai, 1976) since to the best of my knowledge, there are no
sentence parsers of any sort that process this language.Sentence parsing, which is also called syntactic parsing, is the process of identifying
how words can be put together to form correct sentences and determining what
structural role each word plays in the sentence and what phrases are subparts of
what other phrases. A sentence parser outputs a parse structure that could be used
as a component in many applications including semantic analysis, machine
translation, information storage and retrieval of textual data etc.
Today, parsers of different kinds (e.g. probabilistic, rule based) have been developed
for languages, which have relatively wider use nationally and/or internationally (e .g.
English, German, Chinese, etc). The same story is not true for Amharic, the working
language of the Federal Government of Ethiopia, and one of the major languages of
Ethiopia (Bender et ai, 1976) since to the best of my knowledge, there are no
sentence parsers of any sort that process this language. This study, thus, attempted to develop a simple automatic parser for Amharic texts/sentences to address the need for developing systems that automatically process the Amharic language. In the study, the Inside Outside algorithm with a bottom up chart parsing strategy has
been used. The probabilistic context free grammar has been used as a grammatical
formalism to represent the phrase structure rules of the language. A small sample
corpus was selected from sentences in the language, and has been used to serve as
a training and test set. The sample was then hand parsed, automatically tagged, and
was used as a corpus to extract the grammar rules and assign probabilities.
The thesis, in short, describes processes of automatic sentence parsing using a
combination of probabilistic and rule-based reasoning. It describes the whole process
from manually parsing simple sentences to developing a prototype and conducting
an experiment with it. The results obtained using the small manually parsed corpus
seems to encourage further research to be launched, especially with the aim of
developing a full-fledged Amharic sentence parser.
Description
Keywords
Information Science