@article{pub3026,
    abstract = {The information extraction system iDocument 
interactively extracts information 
from texts such as instances and relations with respect to existing 
background knowledge. An extraction process creates weighted 
hypotheses describing indications of relevant information. 
During execution, each process step records its output into an 
instantiated process model. We reused these bits of information 
for generating conceptual, functional 
as well as causal explanations. In order to visualise explanations, 
our component utilises different mechanisms for textual, 
explorative, and pictorial rendering styles.},
    number = {2/08},
    month = {5},
    year = {2008},
    title = {Explanations in the information extraction system iDocument},
    journal = {Künstliche Intelligenz (KI)},
    volume = {Schwerpunkt: Erklärungen},
    pages = {32-34},
    publisher = {Böttcher IT},
    author = {Björn Forcher and Benjamin Adrian and Thomas Roth-Berghofer}
}