Coreference Resolution is the process of identifying all words and phrases in a text that refer to the same entity. It has proven to be a useful intermediary step for a number of natural language processing applications. In this paper, we describe three implementations for performing coreference resolution: rule-based, statistical, and projection-based (from English to German). After a comparative evaluation on benchmark datasets, we conclude with an application of these systems on German and English texts from different scenarios in digital curation such as an archive of personal letters, excerpts from a museum exhibition, and regional news articles.