The Person Cross Document Coreference systems depend on the context for making decisions on the possible coreferences between person name mentions. The amount of context required is a parameter that varies from corpora to corpora, which makes it difficult for usual disambiguation methods. In this paper we show that the amount of context required can be dynamically controlled on the basis of the prior probabilities of coreference and we present a new statistical model for the computation of these probabilities. The experiment we carried on a news corpus proves that the prior probabilities of coreference are an important factor for maintaining a good balance between precision and recall for cross document coreference systems.