Exploring the complexity of natural languages: A fuzzy evaluative perspective on Greenberg universals

In this paper, we introduced a fuzzy model for calculating complexity based on universality, aiming to measure the complexity of natural languages in terms of the degree of universality exhibited in their rules. We validated the model by conducting experiments on a corpus of 143 languages obtained from Universal Dependencies 2.11. To formalize the linguistic universals proposed by Greenberg, we employed the Grew tool to convert them into a formal rule representation. This formalization enables the verification of universals within the corpus. By analyzing the corpus, we extracted the occurrences of each universal in different languages. The obtained results were used to define a fuzzy model that quantifies the degree of universality and complexity of both the Greenberg universals and the languages themselves, employing the mathematical theory of evaluative expressions from fuzzy natural logic (FNL). Our analysis revealed an inversely proportional relationship between the degree of universality and the level of complexity observed in the languages. The implications of our findings extended to various applications in the theoretical analysis and computational treatment of languages. In addition, the proposed model offered insights into the nature of language complexity, providing a valuable framework for further research and exploration.