dkrMorph : A Syriac Morphological Analyzer

Abstract: This thesis proposes a method for automatic morphological analysis of Syriac - an under-resourced language for which there are no natural language processing tools such as morphological analyzers readily available. The proposed method uses a data-driven approach with automatically generated and weighted regular expression rules and patterns to cater for morphological attribute tagging and root- and lexeme derivation for dictionary linkage. The method is compared against a baseline, which it outperforms on all tests, and significantly outperforms for unknown words. When trained on all available training data, the analyzer achieves an accuracy of 95.53%.