In this thesis, we study the importance of background knowledge in relation extraction systems. We not only demonstrate the benefits of leveraging background knowledge to improve the systems' performance but also propose a principled framework that allows one to effectively incorporate knowledge into statistical machine learning models for…

The heart of learning chemistry is the ability to connect a compound's structure to its function; Lewis structures provide an essential link in this process. In many cases, their construction is taught using an algorithmic approach, containing a set of step-by-step rules. We believe that this approach is in direct conflict with the precepts of…