The goal of Informal ion Retrieval has been to reduce human language complexities and as arnresult serve users in The mos I efficient way. The decisive in achieving such end is thernNatural language Processing (NLP). NLP has many components in serving such purpose.rnParsing is one of such components in NLP in improving precision and calligraphic is Therngoal of Informal ion Retrieval Systems. Moreover, parsing is also used inhere{for warlordsrnmachine Translation which is one of the hear of Natural Language Processing. rnToday, difference kinds of parsers have been developed' languages. lhis hare relativelyrnwider use nationally and/or international/ly since The 1960.1. Un[unalterably Gromo has nolrncaptured Ihe advanlage of such .Iyslem being Ihe working language of Ihe Slale Governmentrnof Gromiya, and one of Ihe major languages in Elhiopia and Ababa (Abebe 2002) lor Iherernare no syslems (parsers of any sarI) Ihal parse wril/en lexlS in Ihis language. This siudy is,rnIherefore, an allempl 10 develop a simple aulomalic .lenIence parser for Oromo languagernIn Ihe sludy, Ihe chari algorilhm 11 '0.1 used lI'ilh some modi/iealion. A module (orrnmOlphological analyzer, which splils words inlo roOI form and Iheir wrrespondingrnmorpheme, was also developed in order 10 faeil ilale Ihe preparalion of lexls in a lile 10 bernparsed wilh appropriale lexical calegories. In addition, The unsupervised learning algorilhmrnwas designed 10 guide The parser in predicting unknown and ambiguous words in a sentence.rnGrammar rules, lexicon, morphological rules and lexicon in-formalin were also designedrnon The basis of Ihe review Decide on Ihe linguistic propellers of amII/o grumll1alicalrncategories. This system, facing, is the firslinils kind fiJI' this language. rnThe study adopts an intelligent (Rule-Based+ learning Inodule) approach to develop arnprototype. which is a simple Drama parser/or the language.rnThe thesis. in short. describes processes a/automated sentence parsing oj' Free Texts. Thatrnis, it is aimed at developing a prototype and conducting an experimel with it. The resultrnobtained (95% on the training test and 885% on the test set) using the small manuallyrnparsed sentences encourage birther research to be launched. especially with the aim ofrndeveloping fill~fledged Oromo sentence parser.