1. An article of manufacture comprising a non-transitory computer readable storage medium having computer readable instructions tangibly embodied thereon which, when implemented, cause a computer to carry out a plurality of method steps comprising: determining which documents in a document corpus of multiple documents mention an entity of interest; clustering the documents that mention an entity of interest according to similarities across a temporal signal, a structural signal and a content signal, thereby forming multiple clusters of documents; annotating each document in the multiple clusters of documents with an annotation by marking each occurrence of the entity in each document; calculating a confidence measure for each occurrence of the entity in each document in each of the multiple clusters, wherein said confidence measure comprises the sum of (i) a measure of similarity between the given occurrence of the entity and the entity of interest, and (ii) a measure of similarity between the documents within the cluster of the given document via ∑ j ⁢ x ⁡ ( i , j ) ⁢ sim ⁡ ( i , j ) + ∑ k ⁢ ∑ j ≠ N ⁢ ⁢ A ⁢ x ⁡ ( i , j ) ⁢ x ⁡ ( k , j ) ⁢ sim ⁡ ( i , k ) , wherein x(i, j) indicates mention i being assigned to entity j, sim(i, j) indicates a similarity of mention i to entity j, sim(i, k) indicates a document similarity of mention i and mention k, and NA represents a non-applicable designation; creating a graph for each of the multiple clusters, wherein each of multiple nodes of each graph represents a mention of the entity of interest, and wherein said creating comprises placing an edge between each respective pair of nodes that share a mention, wherein an edge weight attributed to each edge is equal to the similarity between the shared mention; removing said annotation from one or more documents in the multiple clusters of documents by removing said marking for each occurrence of the entity in each document that corresponds to a confidence measure below a given value; and outputting (i) each annotated document and (ii) each created graph.
1. An article of manufacture comprising a non-transitory computer readable storage medium having computer readable instructions tangibly embodied thereon which, when implemented, cause a computer to carry out a plurality of method steps comprising: determining which documents in a document corpus of multiple documents mention an entity of interest; clustering the documents that mention an entity of interest according to similarities across a temporal signal, a structural signal and a content signal, thereby forming multiple clusters of documents; annotating each document in the multiple clusters of documents with an annotation by marking each occurrence of the entity in each document; calculating a confidence measure for each occurrence of the entity in each document in each of the multiple clusters, wherein said confidence measure comprises the sum of (i) a measure of similarity between the given occurrence of the entity and the entity of interest, and (ii) a measure of similarity between the documents within the cluster of the given document via ∑ j ⁢ x ⁡ ( i , j ) ⁢ sim ⁡ ( i , j ) + ∑ k ⁢ ∑ j ≠ N ⁢ ⁢ A ⁢ x ⁡ ( i , j ) ⁢ x ⁡ ( k , j ) ⁢ sim ⁡ ( i , k ) , wherein x(i, j) indicates mention i being assigned to entity j, sim(i, j) indicates a similarity of mention i to entity j, sim(i, k) indicates a document similarity of mention i and mention k, and NA represents a non-applicable designation; creating a graph for each of the multiple clusters, wherein each of multiple nodes of each graph represents a mention of the entity of interest, and wherein said creating comprises placing an edge between each respective pair of nodes that share a mention, wherein an edge weight attributed to each edge is equal to the similarity between the shared mention; removing said annotation from one or more documents in the multiple clusters of documents by removing said marking for each occurrence of the entity in each document that corresponds to a confidence measure below a given value; and outputting (i) each annotated document and (ii) each created graph. 4. The article of manufacture of claim 1 , wherein the method steps comprise training a set of documents with labeled entities to determine a threshold for clustering documents and/or a document similarity weight.