The management of uncertainty is crucial when harvesting structured content from unstructured and noisy sources. Knowledge Graphs (kgs), maintaining both numerical and non-numerical facts supported by an underlying schema, are a prominent example. Knowledge Graph management is challenging because: (i) most of existing kgs focus on static data, thus impeding the availability of timewise knowledge; (ii) facts in kgs are usually accompanied by a confidence score, which witnesses how likely it is for them to hold.
We demonstrate TeCoRe, a system for temporal infer- ence and conflict resolution in uncertain temporal knowledge graphs (utkgs). At the heart of TeCoRe are two state-of-the-art probabilistic reasoners that are able to deal with temporal constraints efficiently. While one is scalable, the other can cope with more expressive constraints. The demonstration will focus on enabling users and applications to find inconsistencies in utkgs. TeCoRe provides an inter- face allowing to select utkgs and editing constraints; shows the maximal consistent subset of the utkg, and displays statistics (e.g., number of noisy facts removed) about the debugging process.
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