Kumova Metin, SenemKişla T.Karaog?lan B.2023-06-162023-06-1620111828-6003https://hdl.handle.net/20.500.14365/4627In this paper, we investigated the features which discriminates verbs in Turkish. Though, words in Turkish can be classified in eight different linguistic categories (noun, verb, adjective, pronoun, adverb, postposition, conjunction and interjection), they can be discriminated in two fundamental groups as nouns and verbs. We have utilized logistic regression method to determine and compare the features based on sentence and word properties considering that all linguistic categories except verbs can be merged into the to the noun originated group. The strength of both categorical (such as inclusion of capital letters, apostrophes) and numerical features (such as position in sentence) in verb discrimination are examined and results are presented. We believe that this study may contribute to the time consuming rule based or probabilistic POS tagging applications since logistic regression analysis gives an immediate foresight of verbs. © 2011 Praise Worthy Prize S.r.l.eninfo:eu-repo/semantics/closedAccessLogistic regressionPOS taggingTurkishFundamental groupLinguistic categoriesLogistic regression analysisLogistic regression methodLogistic regressionsNouns and verbsNumerical featuresPOS taggingRule basedTurkishTurkishsLinguisticsRegression analysisArticle2-s2.0-79953167157