Applying Graphs to Determine the Semantic Network of Basic Persian Verbs

The current interdisciplinary research tries to determine and analyze the semantic network of a part of Persian verbs, by applying graph theory, in the general framework of cognitive linguistics, (cognitive) lexical semantics and computational linguistics.To do this50basic Persian verbs of high frequency were selected from the verified lists of Ebadi etal.(2014),Bijankhan etal.(2014)and Sahraee etal.(2017.The research objective was to identify the strongest and most frequent sense and intra-lingual relations between these verbs by means of the characteristics of the graph drawn by Persian speakers whose mother tongue was also Persian.The statistical population of this field study consisted of Persian-speaking students studying in a ScientificApplied Center as well as those of Sharif University of Technology, and the research sample consisted of101examinees.The research instrument was a nativized questionnaire(including the verbs)which was given to the examinees and they were asked to draw any possible semantic relation between these verbs.By applying Java and Python soft wares, the graph of the extracted data from the questionnaires, the mother(social)graph, was drawn.The findings reveal that the graph’s pattern represents sense relations of synonymy, reverse antonymy, polysemy, entailment (including troponymy (hyponymy) and meronymy as well as causative relation and collocation.From among these, collocation(29.61%)entailment(23.85%)and reverses(16.71%)are themost frequent semantic relations.The achievement of this research is the identification of the semantic network oftheverbs in question in the mental lexicon of thePersian-speakers examinees.Thisnot only canbe used in preparing and compiling better materials for basic lessons of non-Persianspeakers who are learning Persian, but also in applying new educationalmethods suchas teaching verbclusters.