  Systems for automatic extraction of semantic information about events from
large textual resources are now available: these tools are capable to generate
RDF datasets about text extracted events and this knowledge can be used to
reason over the recognized events. On the other hand, text based tasks for
event recognition, as for example event coreference (i.e. recognizing whether
two textual descriptions refer to the same event), do not take into account
ontological information of the extracted events in their process. In this
paper, we propose a method to derive event coreference on text extracted event
data using semantic based rule reasoning. We demonstrate our method considering
a limited (yet representative) set of event types: we introduce a formal
analysis on their ontological properties and, on the base of this, we define a
set of coreference criteria. We then implement these criteria as RDF-based
reasoning rules to be applied on text extracted event data. We evaluate the
effectiveness of our approach over a standard coreference benchmark dataset.
