To build a coreference resolver for a new language, the typical approach is to first coreference-annotate documents from this target language and then train a resolver on these annotated documents using supervised learning techniques. However, the high cost associated with manually coreference-annotating documents needed by a supervised approach makes it difficult to deploy coreference technologies across a large number of natural languages. To alleviate this corpus annotation bottleneck, we examine a translation-based projection approach to multilingual coreference resolution. Experimental results on two target languages demonstrate the promise of our approach.