Generation that exploits corpus-based statistical knowledge
Irene Langkilde, Kevin K. Knight · 1998
We describe novel aspects of a new natural language generator called Nitrogen.This generator has a highly flexible input representation that allows a spectrum of input from syntactic to semantic depth, and shifts' the burden of many linguistic decisions to the statistical post-processor.The generation algorithm is compositional, making it efficient, yet it also handles non-compositional aspects of language.Nitrogen's design makes it robust and scalable, operating with lexicons and knowledge bases of one hundred thousand entities.