Abstract: A linked addendum detection system identifies and links related contractual documents including a master agreement (MA) and associated amendments from a large volume of data. The system extracts primary features including key references or descriptions within each contractual document. In addition, the system also includes grouping to detect the related contractual documents. Moreover, the system sorts the MA and the associated amendments according to the modification time (MTIME), and further sequentially establishes linkages from one contractual document to the next document in order. Furthermore, the system prepares and provides output result for display to an end user.

Abstract: A non-standard and standard clause detection system imports raw input data or contractual documents, and extracts non-standard and standard clauses that are semantically linked. One embodiment of a disclosed configuration is a system and a method for identifying non-standard and standard clauses in contractual documents. The system and the method comprise of generating a primary policy and a secondary policy, obtaining a first feature data set by applying the primary policy to a semantic language evaluator, and obtaining a second feature data set by applying the secondary policy to the semantic language evaluator. The first feature data set obtained is the aggregation of the standard clauses used in the document. Furthermore, the second feature data set encompasses the first feature data set, thus the difference between the first feature data set and the second feature data set is the aggregation of the non-standard clauses.

Abstract: A non-standard and standard clause detection system imports raw input data or contractual documents, and extracts non-standard and standard clauses that are semantically linked. One embodiment of a disclosed configuration is a system and a method for identifying non-standard and standard clauses in contractual documents. The system and the method comprise of generating a primary policy and a secondary policy, obtaining a first feature data set by applying the primary policy to a semantic language evaluator, and obtaining a second feature data set by applying the secondary policy to the semantic language evaluator. The first feature data set obtained is the aggregation of the standard clauses used in the document. Furthermore, the second feature data set encompasses the first feature data set, thus the difference between the first feature data set and the second feature data set is the aggregation of the non-standard clauses.