Explaining Facts Over Knowledge Graphs

Of general interest, linking explanation and knowledge graphs.  Technical.

ExFaKT: a framework for explaining facts over knowledge graphs and text in Acolyer

ExFaKT: a framework for explaining facts over knowledge graphs and text Gad-Elrab et al., WSDM’19

Last week we took a look at Graph Neural Networks for learning with structured representations. Another kind of graph of interest for learning and inference is the knowledge graph.
Knowledge Graphs (KGs) are large collections of factual triples of the form \langle subject\ predicate\ object \rangle (SPO) about people, companies, places etc.

Today’s paper choice focuses on the topical area of fact-checking : how do we know whether a candidate fact, which might for example be harvested from a news article or social media post, is likely to be true? For the first generation of knowledge graphs, fact checking was performed manually by human reviewers, but this clearly doesn’t scale to the volume of information published daily. Automated fact checking methods typically produce a numerical score (probability the fact is true), but these scores are hard to understand and justify without a corresponding explanation.  ... "