Abstract: Processing compliance documents based on an artificial intelligence (AI) model is described herein. A system is configured to obtain a compliance document and obtain seed data associated with the compliance document. The seed data includes a plurality of sample text inputs and a plurality of sample computer readable operations associated with the plurality of sample text inputs. The system is also configured to parse text in the compliance document into one or more text segments, provide the one or more text segments and the seed data to the AI model, and obtain, from the AI model, one or more computer readable operations associated with the one or more text segments. The one or more computer readable operations are generated by the AI model based on few-shot learning using the seed data. The system is also configured to store the one or more computer readable operations for completing the compliance document.

Abstract: A computer implemented method includes obtaining an original graph data structure including multiple stored nodes connected by multiple edges. The stored nodes include multiple operation stored nodes and multiple data stored nodes. The method further includes generating an auxiliary graph data structure from the original graph data structure. The auxiliary graph data structure includes the operation stored nodes. The method further includes executing a pattern mining tool on the auxiliary graph data structure to obtain a pattern list, traversing the auxiliary graph data structure to identify multiple instances of identified patterns in the pattern list, and presenting the instances.

Abstract: A method for reviewing data dependencies in a document that includes requesting an explanation of a dependent data container in a plurality of data containers, in which the dependent data container resides within a document, and receiving the explanation of the dependent data container, in which the explanation that includes information about the dependent data container and information about a precedent data container of the plurality of data containers, and in which the information describes the dependency between the precedent data container and the dependent data container.

Abstract: A method for presenting content in a form including extracting, from an open format for rendering the form, a plurality of elements on the form, wherein the plurality of elements represent the content in the form, identifying a plurality of contextual relationships between the plurality of elements, wherein identifying the plurality of contextual relationships that includes identifying a first attribute of a first element of the plurality of elements, identifying a second attribute of a second element of the plurality of elements, and relating the first element with the second element when a difference between the first attribute and the second attribute is within a predefined threshold, generating a representation of the form, wherein the representation that includes information about the plurality of contextual relationships, and presenting the content in the form based on the representation.

Abstract: A method for automatic code generation that includes obtaining a parse tree, wherein the parse tree represents at least one instruction and wherein the instruction is in a natural language, and wherein the at least one instruction is free-form, determining a plurality of sentence subparts from the parse tree, creating at least one instantiated concept for each of the plurality of sentence subparts, inserting the instantiated concept in an instantiated concept map, traversing the instantiated concept map, wherein traversing the instantiated concept map includes for each instantiated concept in the instantiated concept map obtaining a code output rule according to the instantiated concept, and outputting code according to the code output rule be completed upon finalization of claims.