Design and Implementation of Automatic Morphological Analyzer for Ge’ez Verbs

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Addis Ababa University


Morphological analysis is a crucial component of several natural language processing tasks including machine translation, spell-check, speech recognition, dictionary (lexicon) compilation, POS tagging, etc., especially for languages with a highly complex morphology, where stipulating a full lexicon of surface forms is not feasible. Nowadays, analyzers of different kinds have been developed for languages that have relatively wider use internationally. The same cannot be said for Ge‟ez, the classic language of Ethiopia where majority of the Ethiopian indigenous historical, philosophical, ethical, religious, etc., literatures and ancient manuscripts are written with. This study is, thus, an attempt to design a morphological analyzer model for Ge‟ez verbs thereby contributing to the goal of developing a full-fledged NLP application for Ge‟ez. For this purpose, rule-based approaches specifically CV-based and Two-Level Morphology (TLM) are adopted to design the model and to implement the prototype of the analyzer. Besides, the analyzer uses a knowledgebase as a demon while identifying the morphosyntactic features. Finally, algorithms that take into consideration the morphological, morpho-phonological and orthographic properties of Ge‟ez language are developed from scratch and applied, as there are no previous such attempts. The prototype was tested with verbs which are extracted manually by domain experts from all twenty seven New Testament books of the Ethiopic Version Bible. The accuracy of the output generated by the analyzer was compared with the manually prepared analyses of the same verb-set by the language experts at two levels: at features-of-verbs level and at verb level. Accordingly, it is observed that the analyzer has analyzed these verbs with an accuracy of 92.05% at feature level and of 73.98% at verb level. The analysis output comprises the lexeme and all valued morphosyntactic features including affixes together with their syntactical functions, indicated subjects and objects along with their person-gender-number features, tense-mood and stem type of the verb, etc. At large, this research has realized the design and implementation of automatic morphological analyzer for Ge‟ez verbs. Keywords: Ge‟ez verbs, Ge‟ez verbs analyzer, Morphological Analyzer, Ge‟ez Morphology



Ge‟Ez Verbs, Ge‟Ez Verbs Analyzer;Morphological Analyzer;Ge‟Ez Morphology