dkrMorph: A Syriac Morphological Analyzer
Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
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%.
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IdentifiersURN: urn:nbn:se:uu:diva-154515OAI: oai:DiVA.org:uu-154515DiVA: diva2:421003
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