Large scale experiments on Freebase and a Wikipedia/NY Times corpus show that jointly embedding brings promising improvement in the accuracy of predicting facts, compared to separately embedding knowledge graphs and text.
jointly embedding enables the prediction of facts containing entities out of the knowledge graph, which cannot be handled by previous embedding methods.