Identification of Choice Sets (CSs) is a crucial step towards the estimation of public transport route choice models. However, identification of reliable CSs is a challenging task as the routes considered by travelers are not directly observed. To handle this issue, this study adopts an existing Choice Set Generation Methodology (CSGM) for the identification of CSs by using General Transit Feed Specification (GTFS) data. The final feasible CSs are then compared to the actual passengers' choices observed in Smart Card Data (SCD) by using three validation metrics; passenger and network coverage as well as network efficiency. The aim of the study is to shed light on the performance of a CSGM in Stockholm's multimodal transit network by using data retrieved by different Intelligent Transportation System (ITS) applications focused on operations and on ridership automated data collection. However, the use of CSGM for large networks raises scalability and computational issues. In this direction, the study also contributes in the implementation of the CSGM in a larger network compared to existing case studies.