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Yayın All-words word sense disambiguation in Turkish(Işık Üniversitesi, 2019-09-06) Akçakaya, Sinan; Yıldız, Olcay Taner; Işık Üniversitesi, Fen Bilimleri Enstitüsü, Bilgisayar Mühendisliği Yüksek Lisans ProgramıWord sense disambiguation (WSD) is the identi cation of the meaning of words in context in a computational manner. The main subject of this study is to implement and compare the WSD results of various supervised classi ers (Naive Bayes, K Nearest Neighbor, Rocchio and C4.5) in all-words setting. To this end, we have constructed an all-words sense annotated Turkish corpus, using traditional method of manual tagging. During the annotation, a pre-built parallel treebank (aligned from Penn Treebank) has been tagged with the senses of Turkish Language Institutions dictionary. The approach of annotating a treebank allowed us to generate a full-coverage resource, in which syntactic and semantic information merged. In the WSD evaluations, three distinct experiments have been organized to determine the efect of using different feature sets on the disambiguation performance. First experiment has been conducted with a simple feature set that includes the fundamental local features. In the second experiment, the initial feature set has been augmented with several effective morphological features, and in the third one, the feature set has further been extended with the syntactic features. Our test results show that all classi ers have achieved better results in parallel to growing feature set. Additionally, integration of syntactic features has proved to be useful for WSD.
