A Short Review of Abstract Meaning Representation Applications

Abstract Meaning Representation (AMR) is a representation model in which AMRs are rooted and labeled graphs that capture semantics on the sentence level while abstracting away from Morpho-Syntactic properties. The nodes of the graph represent meaning concepts and the edge labels show relationships between them. The application of AMR, as a principal form of structured sentence semantics, in Natural Language Processing (NLP) tasks is widely increasing, and it is considered a turning point for NLP research. The present study gives a brief review of the existing AMR applications in various NLP tasks. Moreover, they are compared and some of their basic features are discussed.