Modeling N-ary relational data as gyro-polygons with learnable gyro-centroid

Binary Knowledge base (KB) embedding has been broadly studied, while n-ary relational KB embedding which aims to simultaneously map binary and beyond-binary facts into low-dimensional vector space is less explored. Existing n-ary KB embedding approaches typically treat entities in n-ary fact as equally important or decompose n-ary relational fact into subtuples. And they generally model n-ary relational KBs in the