An Automatic Sentence Parser for Oromo Language using Supervised Learning Technique
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Date
2002-06
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Addis Ababa University
Abstract
The goal of Information Retrieval has been to reduce human language complexities and as a
result serve users in the most efficient way. The decisive tool in achieving such end is the
Natural language Processing (NLP). NLP has many components in serving such purpose.
Parsing is one of such components in NLP in improving precision and recall which is the
goal of Information Retrieval Systems. Moreover, parsing is also used in the effort towards
machine translation which is one of the heart of Natural Language Processing.
Today, different kinds of parsers have been developed for languages, which have relatively
wider use nationally and/or internationally since the 1960s. Unfortunately Oromo has not
captured the advantage of such system being the working language of the State Government
of Oromiya, and one of the major languages in Ethiopia and Africa (Abebe 2002) for there
are no systems (parsers of any sort) that parse written texts in this language. This study is,
therefore, an attempt to develop a simple automatic sentence parser for Oromo language.
In the study, the chart algorithm was used with some modification. A module for
morphological analyzer, which splits words into root form and their corresponding
morpheme, was also developed in order to facilitate the preparation of texts in a file to be
parsed with appropriate lexical categories. In addition, the unsupervised learning algorithm
was designed to guide the parser in predicting unknown and ambiguous words in a sentence.
Grammar rules, lexicon, morphological rules and contextual information were also designed
on the basis of the review made on the linguistic properties of Oromo grammatical
categories. This system, in fact, is the first in its kind for this language.
The study adopts an intelligent (Rule-Based+ learning module) approach to develop a
prototype, which is a simple Oromo parser for the language.
The thesis, in short, describes processes of automated sentence parsing of Free Texts. That
is, it is aimed at developing a prototype and conducting an experiment with it. The result
obtained (95% on the training test and 88.5% on the test set) using the small manually
parsed sentences encourage further research to be launched, especially with the aim of
developing a full-fledged Oromo sentence parser.
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Keywords
Automatic Sentence Parser