  When spreadsheets are filled freely by knowledge workers, they can contain
rather unstructured content. For humans and especially machines it becomes
difficult to interpret such data properly. Therefore, spreadsheets are often
converted to a more explicit, formal and structured form, for example, to a
knowledge graph. However, if a data maintenance strategy has been missing and
user-generated data becomes "messy", the construction of knowledge graphs will
be a challenging task. In this paper, we catalog several of those challenges
and propose an interactive approach to solve them. Our approach includes a
graphical user interface which enables knowledge engineers to bulk-annotate
spreadsheet cells with extracted information. Based on the cells' annotations a
knowledge graph is ultimately formed. Using five spreadsheets from an
industrial scenario, we built a 25k-triple graph during our evaluation. We
compared our method with the state-of-the-art RDF Mapping Language (RML)
attempt. The comparison highlights contributions of our approach.
