1. A method for coreference resolution comprising: receiving a set of document clusters, each cluster in the set of document clusters comprising a set of text documents; identifying instances of each of a set of candidate named entities in the document clusters, the instances of a respective candidate named entity being text elements; for each of the candidate named entities, generating an event profile, the event profile comprising an optionally normalized vector of size k, where k is the number of document clusters in the set, in which each index of the vector is based on the occurrences of the identified instances of the candidate named entity in a respective one of the k clusters; with a processor, computing a similarity between a pair of the candidate named entities based on their respective event profiles; and providing a decision for merging of the candidate named entities into a common real named entity, based on the computed similarity.
1. A method for coreference resolution comprising: receiving a set of document clusters, each cluster in the set of document clusters comprising a set of text documents; identifying instances of each of a set of candidate named entities in the document clusters, the instances of a respective candidate named entity being text elements; for each of the candidate named entities, generating an event profile, the event profile comprising an optionally normalized vector of size k, where k is the number of document clusters in the set, in which each index of the vector is based on the occurrences of the identified instances of the candidate named entity in a respective one of the k clusters; with a processor, computing a similarity between a pair of the candidate named entities based on their respective event profiles; and providing a decision for merging of the candidate named entities into a common real named entity, based on the computed similarity. 16. The method of claim 1 , further comprising re-clustering the documents based on the updated named entity database.