Analysis Tool for UNL-Based Knowledge Representation
This work addresses the need for language-independent knowledge representation tools, but it is incremental as it builds on existing UNL frameworks without major breakthroughs.
The paper tackles the problem of making knowledge representation accessible across languages by developing a graphical tool that uses the Universal Networking Language (UNL) to visually represent semantic data from native texts, converting UNL conceptual hyper-graphs into XML and then into graphs.
The fundamental issue in knowledge representation is to provide a precise definition of the knowledge that they possess in a manner that is independent of procedural considerations, context free and easy to manipulate, exchange and reason about. Knowledge must be accessible to everyone regardless of their native languages. Universal Networking Language (UNL) is a declarative formal language and a generalized form of human language in a machine independent digital platform for defining, recapitulating, amending, storing and dissipating knowledge among people of different affiliations. UNL extracts semantic data from a native language for Interlingua machine translation. This paper presents the development of a graphical tool that incorporates UNL to provide a visual mean to represent the semantic data available in a native text. UNL represents the semantics of a sentence as a conceptual hyper-graph. We translate this information into XML format and create a graph from XML, representing the actual concepts available in the native language