Patent Document ID: 9785696
Application ID: 14059830

Base Claim:
1. A computer system comprising: memory storing: a target data graph, and a plurality of source data graphs generated from analysis of source documents, where each source data graph: is associated with a source document having an associated domain, has a source entity that does not exist in the target data graph but has an entity type that exists in the target data graph, and includes fact tuples, where a fact tuple identifies: a subject entity, a relationship connecting the subject entity to an object entity, wherein the relationship is associated with the entity type of the subject entity in the target data graph, and the object entity; at least one processor; and memory storing instructions that, when executed by the at least one processor, cause the computer system to perform operations including: generating a cluster of source data graphs, the cluster including source data graphs associated with a first source entity of a first source entity type that shares at least two fact tuples that have the first source entity as the subject entity and a determinative relationship as the relationship connecting the subject entity to the object entity, iteratively splitting the source data graphs in the cluster into a plurality of buckets of the source data graphs based on a plurality of fact tuples, wherein each iteration operates on a distinct determinative relationship and each of the buckets for the iteration includes source data graphs that share a value for the fact tuple, discarding one or more buckets from the cluster that are associated with less than a minimum number of domains represented by the source data graphs in the cluster, generating a reconciled graph by merging the source data graphs remaining in the cluster when the source data graphs meet a similarity threshold, and generating a suggested new entity and entity relationships for the target data graph based on the reconciled graph.

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Claim 4:
4. The system of claim 1 , wherein the similarity threshold is based on a quantity of fact tuples for a first source data graph in the cluster that match fact tuples for a second source data graph in the cluster.