International Business Machines Corporation

Eman Omar

Craig M Trim

Victoria O Odeyemi

Ahmed M A Nassar

Andrew Ronald Freed

Ahmed M Nassar

For confidence weighting relationships between complex entities in unstructured data an expressed relationship between a subset of a set of tokens is extracted from a knowledge graph corresponding to the unstructured data. The knowledge graph includes the set of tokens. The tokens in the subset of tokens are related in the expressed relationship by a set of predicates. A number of occurrences of the set of predicates in the unstructured data is determined. A number of occurrences of the expressed relationship in the unstructured data is determined. Using the number of occurrences of the set of predicates and the number of occurrences of the expressed relationship, a confidence value is computed and assigned to the expressed relationship.

Confidence weighting of complex relationships in unstructured data

A method, system, and computer program product for identifying related information in dissimilar data are provided in the illustrative embodiments. Using a first part of a first entry in a dictionary, a first portion is identified in a first data, the first part matching the first portion within a tolerance. A second part of the first entry referencing a section of a second data is determined, the second data being organized in a repository according to a schema. A third part of the first entry sufficient to locate a record in the section of the second data is determined. A query is constructed using the second part and the third part, and performed on the second data. A result set is obtained, wherein a record in the result set is related to the first portion in the first data and the record does not include the first portion.

Identifying related information in dissimilar data

To extract relationships between complex entities from unstructured data, a parser parses, using an existing language model, the unstructured data to generate a parse tree. From the parse tree, a set of tokens is created. A token in the set of tokens includes a set of words found in the unstructured data. The set of tokens is inserted in the existing language model to form an enhanced language model. The unstructured data is re-parsed using the enhanced language model to create a knowledge graph. From the knowledge graph, a relationship between a subset of the set of tokens is extracted.

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Eman Omar