Comparative analysis of Russian and Persian otadjectival syntactic derivatives denoting color

The article provides a comparative analysis of Russian syntactic derivatives formed from adjectives with color semantics and their analogues in the Persian language. The study focuses on twelve basic color terms that are accepted in Russian and Persian languages, such as: white ( سفید sefid), black ( سیاه siyāh), yellow ( زرد zard), red ( قرمز qermez, سرخ sorx), green ( سبز sabz), purple ( بنفش banafš), pink ( صورتی surati), orange ( نارنجی nārenji), blue ( آبی ābi), light blue ( نیلگون nilgun), gray ( خاکستری xākestari) and brown ( قهوه ای qahve’i) (as defined by B. Berlin and P. Kay). The article explores the structural and semantic similarities and differences between these deadjectival derivatives in Russian and their equivalents in Persian. The theoretical part of the article presents the views of some of the most prominent Russian and Iranian scholars, linguists, and researchers who have contributed to the study of this topic. The purpose of this study is to assist Russian and Iranian students in overcoming the difficulties they encounter when translating these derivative words. During the research, a descriptive approach to linguistic analysis was employed, including the observation and comparison of linguistic data obtained from the National Corpus of the Russian Language (NCRL). As a result of the analysis, it was revealed that Russian deadjectival nouns representing color are characterized by two meanings: abstract and objectified, while Persian ones also have the meaning of infinitives. The article offers recommendations for the correct translation of these derivative words. The findings of this research can be utilized in research and translation efforts, as well as for clarifying the meanings of Russian deadjectival derivatives denoting color in both Russian-Persian and Persian-Russian bilingual dictionaries. In addition, the findings can be beneficial for enhancing online dictionary databases and enhancing the accuracy of neural machine translation. However, it should be noted that this issue has not been thoroughly investigated and requires further study.