Scoring the performance of a system is an extremely important aspect of coreference algorithm performance. The score for a particular run is the single strongest measure of how well the system is performing and it can strongly determine directions for further improvements. In this paper, we present several di erent scoring algorithms and detail their respective strengths and weaknesses for varying classes of processing. In particular, we describe and analyze the coreference scoring algorithm used to evaluate the coreference systems in the sixth Message Understanding Conference (MUC-6)[MUC-6, 95]. We also present two shortcomings of this algorithm. In addition, we present a new coreference scoring algorithm, our B-CUBED algorithm, which was designed to overcome the shortcomings of the MUC-6 algorithm.