Detecting inflectional patterns for Croatian verb stems using class activation mappings

Abstract

All verbal forms in the Croatian language can be derived from two basic forms: the infinitive and the present stems. In this paper, we present a neural computation model that takes a verb in an infinitive form and finds a mapping to a present form. The same model can be applied vice-versa, i.e. map a verb from its present form to its infinitive form. Knowing the present form of a given verb, one can deduce its inflections using grammatical rules. We experiment with our model on the Croatian language, which belongs to the Slavic group of languages. The model learns a classifier through these two classification tasks and uses class activation mapping to find characters in verbs contributing to classification. The model detects patterns that follow established grammatical rules for deriving the present stem form from the infinitive stem form and vice-versa. If mappings can be found between such slots, the rest of the slots can be deduced using a rule-based system.

Keywords

• Croatian infinitive and present verb stems
• convolutional neural network
• class activation mapping