Common sense is knowledge that most humans have, but machines do not. Generally, computer knowledge bases make use of positive (known) knowledge. However, in addition to positive common sense knowledge, there is also negative. Negative knowledge represent facts that are known to be untrue, like "a cat does not have fins". This knowledge is important in order for a machine to make assumptions the same way a human does. This research proposes ways to combine and organize the positive and negative knowledge tuples in a unified way. The two main ways that are looked into are table-like and graph-like organizations. These are analyzed based on different requirements and important queries are defined. Based on the requirements a recommendation is made. The research also takes a look at a solution that makes use of complex number space and suggest how this solution could be further researched and improved in the future.