Building a geo-historical reference dataset of geographical entities enables a wide range of applications, such as the study of urban dynamics. Several approaches in the literature demonstrate the feasibility of constructing such references, but they typically require structured and homogeneous datasets at multiple points in time, also known as snapshots. However, the increasing availability of digitized archival sources, combined with advances in information extraction methods, now makes it possible to produce large volumes of heterogeneous, fragmented, and incomplete data about past geographic entities and their evolution. Existing approaches to building geo-historical reference datasets are not yet well suited to integrating such data in a satisfactory way. In this paper, we propose a method to reconstruct the spatio-temporal evolution of geographic entities from heterogeneous and fragmented data originating from various sources. We also explain how the consistency of the resulting data graph is ensured. Finally, we evaluate our method by applying it on an area in the east of Paris, using sources spanning from the 18th century to the present day.