We present KB-UNIFY, a novel approach for integrating the output of different Open Information Extraction systems into a single unified and fully disambiguated knowledge repository. KB-UNIFY con-sists of three main steps: (1) disambigua-tion of relation argument pairs via a sense-based vector representation and a large unified sense inventory; (2) ranking of se-mantic relations according to their degree of specificity; (3) cross-resource relation alignment and merging based on the se-mantic similarity of domains and ranges. We tested KB-UNIFY on a set of four heterogeneous knowledge bases, obtain-ing high-quality results. We discuss and provide evaluations at each stage, and re-lease output and evaluation data for the use and scrutiny of the community1. 1