Performing numerical analysis successfully depends on several factors. One of the most important factors is determining the constitutive model parameters correctly. It is often the case that these parameters are determined based on limited soil data. Using in-situ tests for determining these parameters has several advantages such as minimal disturbance of the soil and lower cost compared to laboratory tests. However, it is not possible to determine soil parameters directly from in-situ tests results. Thus, empirical correlations are required for interpreting soil parameters. Generally, several correlations exist for the same parameter, which will lead to calculating several values for the same parameter. An ongoing research project focuses on formulating an automated parameter determination (APD) framework that uses a graph-based approach to identify constitutive model parameters based on in-situ tests. This is achieved by using two spreadsheets as an input, one for parameters and the other for equations (correlations used to calculate parameters). Based on these two spreadsheets, the system generates paths between the parameters and calculates the value(s) for each individual parameter. So far, the research project focused on determining the parameters for coarse-grained soil based on cone penetration test (CPT) results. Due to the fact that the system was set up in a modular and adaptable way, it is possible to expand the system to accommodate more soil types and in-situ tests. It is the aim of the research project to increase the reliability of the parameters values (required to perform numerical analysis) determined from in-situ tests. This paper focuses on expanding the current framework to determine parameters for fine-grained soil. By using the two spreadsheets as an input, the system successfully calculates the value(s) for fine-grained parameters. Further validation, dealing with several values for each parameter, determining the accuracy of derived parameters and expanding the system to accommodate other in-situ tests and types of soils are part of ongoing research.