Learning and Inference in Entity and Relation Identification

In this study, I examine several different approaches to identifying entities and relations in sentences. I compare three different strategies to learn entities and relations. The first uses just local classifiers, the second uses local classifiers with integer linear programming (ILP) inference, and the third uses inference based training (IBT) and evaluates using ILP inference. My experiments indicate that in solving this particular problem, IBT performs the others, followed by local classifiers with (ILP) inference, and lastly the local classifiers by themselves. However these differences are not as large as one might expect.