Improving Nominalized Adjectives Tagging



Year of publication 2019
Type Appeared in Conference without Proceedings
MU Faculty or unit

Faculty of Arts

Description Part of speech transitions represent an interesting issue in terms of Automatic Morphological Analysis (AMA). In these cases, two parts of speech have to be considered: initial and final. However, their automatic recognition is complicated by the same form. This article presents the results of a corpus study aimed at mapping nominalized adjectives tagging with a focus on detecting candidates for nominalization among frequent adjectives. Analysis of the data obtained from the ČNK SYN v5 corpus shows different reasons for incorrect tagging. Taking into account these reasons, we propose three solutions for the improvement nominalized adjectives tagging.
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