So What's the Plan? Mining Strategic Planning Documents
This work addresses the need for language technology tools in e-government research, but it is incremental as it applies existing methods to a new dataset.
The authors tackled the problem of analyzing strategic planning documents by creating RuREBus, a corpus of Russian strategic planning documents, and developed a pipeline for corpus creation using a human-in-the-loop annotation strategy, resulting in a large annotated dataset that enables insights into e-government research.
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.