Computer implemented method for the automated analysis or use of data

A computer-based system configured to analyse data, the system being configured to:

• (a) store in a non-transitory storage medium, or access in a non-transitory storage medium, a structured, machine-readable representation of data that conforms to a machine-readable processable language, wherein the language has a syntax in which the syntax for the machine-readable processable language is an unambiguous syntax comprising nesting of structured, machine-readable representations of data;
• in which the structured, machine-readable representation of data that conforms to the machine-readable processable language comprises semantic nodes and passages;
• and in which a semantic node represents an entity and is represented by an identifier;
• and a passage is either (i) a semantic node or (ii) a combination of semantic nodes;
• and in which machine-readable meaning comes from choice of semantic nodes and the way the semantic nodes are combined and ordered as passages;
• wherein the structured machine-readable representation of data includes passages that represent reasoning statements, wherein the passages that represent the reasoning statements are represented in the processable language to represent semantics of reasoning steps;
• (b) automatically process the structured, machine-readable representation to learn, in which the learning is different to statistical machine-learning, wherein the learning takes place using at least a plurality of the reasoning steps, in which semantic nodes and passages that are generated using at least the plurality of the reasoning steps, are stored and utilised;
• and
• (c) store a result of the learning in the structured, machine-readable representation.

A computer program product embodied on a first non-transitory storage medium, the computer program product executable on a processor to:

• (a) access in a second non-transitory storage medium a structured, machine-readable representation of data that conforms to a machine-readable processable language, wherein the processable language has a syntax in which the syntax for the machine-readable processable language is an unambiguous syntax comprising nesting of structured, machine-readable representations of data;
• in which the structured, machine-readable representation of data that conforms to the machine-readable processable language comprises semantic nodes and passages;
• and in which a semantic node represents an entity and is represented by an identifier;
• and a passage is either (i) a semantic node or (ii) a combination of semantic nodes;
• and in which machine-readable meaning comes from choice of semantic nodes and the way the semantic nodes are combined and ordered as passages;
• wherein the structured machine-readable representation of data includes passages that represent reasoning statements, wherein the passages that represent the reasoning statements are represented in the processable language to represent semantics of reasoning steps;
• (b) automatically process the structured machine-readable representation of data that conforms to the machine-readable processable language, to learn, in which the learning is different to statistical machine-learning, wherein the learning takes place using at least a plurality of the reasoning steps, in which semantic nodes and passages that are generated using at least the plurality of the reasoning steps, are stored and utilised, and
• (c) store a result of the learning in the structured, machine-readable representation.