7. The method of claim 1 , wherein each of the first clusters includes a list of all organization entities in the cluster; the geopolitical entities of the cluster which is a set union of all geopolitical entities of the organization entities in the cluster; a distance matrix containing inter-component distances defined using a string similarity metric; and a centroid string where the centroid string is equal to organization entity which possesses the least sum of distances from all organization entities in the cluster.
1. In an apparatus, a method of extracting, merging, and systematizing organization names from text, comprising: at a computer-readable medium having one or more microprocessors configured to host and execute one or more programs, extracting organization-related text from a database; identifying one or more phrases contained in said text; associating organization entities with at least one country, email address, URL, street address, city, or state of a portion of said phrases based upon the content of said phrases; assigning at least a portion of the remaining phrases as organization entities, based upon the content of said phrases and whether nearby phrases have been assigned as organization entities; performing a first unsupervised clustering wherein said organization entities are grouped into a first plurality of clusters based upon geopolitical entity and a modified edit distance metric, wherein each of the first clusters includes a list of all organization entities in the cluster; wherein each new organization entity under consideration is compared to the centroids of all clusters having the same geopolitical entity, wherein if the modified edit distance metric indicates that the described organization entity, under consideration, matches above a predetermined threshold to the centroid of a cluster, then the described organization entity under consideration is added to that cluster, wherein if the described organization entity does not match above a predetermined threshold to the centroid of any existing cluster, then that described organization entity becomes the centroid of a new cluster; performing a second unsupervised clustering wherein said first plurality of clusters are clustered into one or more second clusters based upon geopolitical entity and at least one similarity metric based on centroids of said first plurality of clusters, wherein the second unsupervised clustering includes connected components clustering, wherein the second unsupervised clustering groups organization entities which represent the same organization despite being having substantially different words; and designating a normalized organization name for each second cluster based upon predetermined criteria.