Abstract: A semantic data processing system for processing an unstructured data file based on semantics of textual content of the unstructured data file comprises a processing arrangement configured to: receive, structured reference data, via reference data ingester; receive unstructured data files via an unstructured data file preprocessor: generate, via knowledge graph generator, knowledge graph from the structured reference data using structure of the structured reference data, the knowledge graph specifying a plurality of different entities having relationships with each other and relationship data linking the different entities; generate, via entity-centric search query generator, entity-centric search query by using the knowledge graph, the entity-centric search query specifying plurality of entity-related textual terms and parameters regarding the relationships between the entity-related textual terms; and execute, via contextual matching engine, the entity-centric search query on the received unstructured data

Abstract: A system for inducing taxonomy based on a data sample and an inference classification of raw data (506A) using the induced taxonomy (IT). includes processing arrangement (PA) (106) using set of modules selected from: a segmentation module configured to segment data sample into ontological segments a clustering module configured to cluster ontological segments into ontological clusters (206); a subtree generation module configured to large language model to generate subtree (208, 302) for each ontological cluster; and a taxonomy construction module configured to induce taxonomy comprising root node (210A, 302A, 304A, 702) and combination of subtrees. The PA includes a classification module configured to map IT to set of label configuration objects (504A, 602A-D); and classify raw data using a set of label configuration objects derived from mapped IT. Included is computer-implemented method for inducing taxonomy based on data sample and inference classification of raw data using IT.

Abstract: A method for generating perspective(s) of a knowledge graph includes receiving the knowledge graph from a database, wherein the knowledge graph includes vertices at least partially connected together by edges; generating a property graph of the knowledge graph, including vertices at least partially connected together by edges; creating metagraph transformation(s) to be executed on the property graph for generating perspective(s) of the knowledge graph, wherein each metagraph transformation is lazily evaluated on the property graph; validating at least one metagraph transformation based on the lazy evaluation of on the property graph against a set of user-defined schema configurations; detecting a set of errors in the at least one metagraph transformation, if the at least one metagraph transformation is not successfully validated against the set of user-defined schema configurations; and displaying the set of errors to a user for adjusting the at least one metagraph transformation

Abstract: There is disclosed a method for generating perspective(s) (300) of a knowledge graph (302).