The Sequence Notation: Catching Complex Meanings in Simple Graphs

Current symbolic semantic representations proposed to capture the semantics of human language have served well to give us insight in how meaning is expressed. But they are either too complicated for large-scale annotation tasks or lack expressive power to play a role in inference tasks. What I propose is a meaning representation system that it is inter-lingual, model-theoretic (by translation to first-order logic), and variable-free. It divides the labour involved in representing meaning along three levels: concept, roles, and contexts. As natural languages are expressed as sequences of phonemes or words, the meaning representations that I propose are likewise sequential. However, the resulting meaning representations can also be visualised as directed acyclic graphs.