16. A method of automatically identifying new entities for a target data graph comprising: generating, for each of a plurality of text documents, a source data graph for a potential entity from the text document in which the potential entity is identified, the source data graph representing the potential entity and facts about the potential entity from the text document and the text document being hosted at a domain, wherein the target data graph lacks the potential entity but an entity type of the potential entity exists in the target data graph; clustering source data graphs by entity name and type, wherein at least one cluster is for the potential entity; iteratively dividing the cluster into a plurality of buckets of source data graphs based on a plurality of fact tuples, wherein each of the plurality of fact tuples includes a subject entity matching the potential entity and a distinct determinative relationship; verifying the potential entity using the cluster by: corroborating at least a quantity of determinative facts about the potential entity, and determining the potential entity is included in a bucket associated with a minimum number of different domains represented by the source data graphs in the bucket after iteratively dividing the cluster; and storing the potential entity and the facts about the potential entity.
16. A method of automatically identifying new entities for a target data graph comprising: generating, for each of a plurality of text documents, a source data graph for a potential entity from the text document in which the potential entity is identified, the source data graph representing the potential entity and facts about the potential entity from the text document and the text document being hosted at a domain, wherein the target data graph lacks the potential entity but an entity type of the potential entity exists in the target data graph; clustering source data graphs by entity name and type, wherein at least one cluster is for the potential entity; iteratively dividing the cluster into a plurality of buckets of source data graphs based on a plurality of fact tuples, wherein each of the plurality of fact tuples includes a subject entity matching the potential entity and a distinct determinative relationship; verifying the potential entity using the cluster by: corroborating at least a quantity of determinative facts about the potential entity, and determining the potential entity is included in a bucket associated with a minimum number of different domains represented by the source data graphs in the bucket after iteratively dividing the cluster; and storing the potential entity and the facts about the potential entity. 20. The method of claim 16 , wherein the minimum number of different domains depends on the number of domains represented by the text documents.