  In this paper we present a corpus of Russian strategic planning documents,
RuREBus. This project is grounded both from language technology and
e-government perspectives. Not only new language sources and tools are being
developed, but also their applications to e-goverment research. We demonstrate
the pipeline for creating a text corpus from scratch. First, the annotation
schema is designed. Next texts are marked up using human-in-the-loop strategy,
so that preliminary annotations are derived from a machine learning model and
are manually corrected. The amount of annotated texts is large enough to
showcase what insights can be gained from RuREBus.
