A semantic document generation and search system is described. A collection of documents is received and a categorization of the contents of documents is generated using a first language model. The categorization is input into a second language model to extract terms from each document of the collection of documents. A knowledge graph is generated for each document, each knowledge graph having a plurality of nodes corresponding to the extracted terms from each document. The knowledge graphs are linked to each other by common terms to form a collection of knowledge graphs. When a new document is received, the terms from the new document are extracted using the first categorization as input to the second language model. A new knowledge graph is generated for the new document, and linked to the knowledge graphs in the collection of knowledge graphs using common terms.
A semantic document generation and search system is described. The semantic document extraction system generates a knowledge graph representing a collection of documents, each document being represented as a sub-graph of the knowledge graph being linked to each other by common terms of a plurality of document terms. The system extracts a first filter criterion based on the plurality of terms of the sub-graphs representing the collection of documents, receives a first search value for the first filter criterion, and identifies a subset of sub-graphs, of the knowledge graph, that include a term corresponding to the first filter criterion and having a term value corresponding to the first search value. The system prunes the knowledge graph to include only the identified subset of sub-graphs, and extracts and outputs a subset of the collection of documents corresponding to the subset of sub-graphs included in the pruned knowledge graph.
A semantic document generation and search system is described. The semantic document extraction system generates a knowledge graph representing a collection of documents, each document being represented as a sub-graph of the knowledge graph being linked to each other by common terms of a plurality of document terms. The system extracts a first filter criterion based on the plurality of terms of the sub-graphs representing the collection of documents, receives a first search value for the first filter criterion, and identifies a subset of sub-graphs, of the knowledge graph, that include a term corresponding to the first filter criterion and having a term value corresponding to the first search value. The system prunes the knowledge graph to include only the identified subset of sub-graphs, and extracts and outputs a subset of the collection of documents corresponding to the subset of sub-graphs included in the pruned knowledge graph.
A semantic document generation system is described. The semantic document is composed of document details, people and meta-data. The semantic document is self-aware of the information it contains. The semantic document's structure and terms are governed by legal, logical and party related rules. A semantic contract can be created from a semantic document generation system. The semantic document generation system receives an indication of a type of a document to be generated and plurality of terms for the document from a plurality of sources. The terms are converted into triples. A plurality of rules governing the terms of the document is applied to the triples to generate a knowledge graph and determine whether terms from the different parties are compatible. The terms are determined to be compatible in a case where the plurality of rules governing terms of the document is satisfied. If at least one set of terms is non-compatible, the system reconciles the non-compatible terms in the generated knowledge graph until all the terms are compatible, and generates the document based at least on the reconciled knowledge graph.
A semantic document generation system is described. The semantic document is composed of document details, people and meta-data. The semantic document is self-aware of the information it contains. The semantic document's structure and terms are governed by legal, logical and party related rules. A semantic contract can be created from a semantic document generation system. The semantic document generation system receives an indication of a type of a document to be generated and plurality of terms for the document from a plurality of sources. The terms are converted into triples. A plurality of rules governing the terms of the document is applied to the triples to generate a knowledge graph and determine whether terms from the different parties are compatible. The terms are determined to be compatible in a case where the plurality of rules governing terms of the document is satisfied. If at least one set of terms is non-compatible, the system reconciles the non-compatible terms in the generated knowledge graph until all the terms are compatible, and generates the document based at least on the reconciled knowledge graph.
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