<figure xmlns="http://www.tei-c.org/ns/1.0"><graphic url="134_final-1bc538a7b3f4ef1425ec82e9256a9fdf.png" /><head>Tabelle 2: Results of the rule-based algorithm without user-specified knowledge and with user-specified knowledge provided by two different annotators (D and M) on six randomly picked documents of DROC. The last three lines show the average improvement of the annotators.</head></figure>Depending on the text snippet, the improvements range from 0% up to almost 11% B-Cubed and up to 2% MUC score with an average improvement of about 4% B-Cubed. The small improvement of the MUC metric means, that with the help of the meta data, only relatively few links are improving, but these links reveal to be among the important ones, when the results of the B-Cubed metric is consulted. The improvements are mainly due to the improvements of the Recall, our algorithm is tuned to produce a conservative output and therefore does not attempt to merge references or entities that pose a high risk of failure. The usage of meta data adds to the confidence for these merges and subsequently increases the Recall.