language: en

Generating Word Lattices from Abstract Meaning Representation

Irene Langkilde and Kevin Knight
Information Sciences Institute University of Southern California
Marina del Rey, CA 90292
ilangkil@isi.edu and knight@isi.edu

Abstract Large-scale generation of natural language requires an abstract meaning representation and a mechanism for integrating immense amounts of lexical, morphological, grammatical, and conceptual knowledge. The availability of corpus-based statistical knowledge motivates the invention of a new style of generation in which word lattices compactly encode many possible sentence renderings and a statistical extractor chooses the best ones. The focus of generation thus shifts to how word lattices can be generated from abstract meaning representation. This paper presents a flexible meaning representation scheme and generation mechanism. It includes an efficient generation algorithm and grammar formalism that maps from a meaning representation to a lattice. This mapping is flexible enough to allow meaning representation along a continuum of semantic depth.

Introduction