Methods of estimating the number of clusters for person cross document coreference task

Knowing the number of different individuals carrying the same name may improve the overall accuracy of a Person Cross Document Coreference System, which processes large corpora and clusters the name mentions according to the individuals carrying them. In this paper we present a series of methods of estimating this number. In particular, an estimation method based on name perplexity, which brings a large improvement over the baseline given by the gap statistics, is instrumental in reaching accurate clustering results because not only it can predict the number of clusters with a very good confidence, but also it can indicate what type of clustering method works best for each particular name.