Parsing Graphs with Hyperedge Replacement Grammars

David Chiang, Jacob Andreas, Daniel Bauer, Karl Moritz Hermann, Bevan K. Jones, Kevin Knight

Abstract: Hyperedge replacement grammar (HRG) is a formalism for generating and transforming graphs that has potential applications in natural language understanding and generation. A recognition algorithm due to Lautemann is known to be polynomial-time for graphs that are connected and of bounded degree. We present a more precise characterization of the algorithm’s complexity, an optimization analogous to binarization of contextfree grammars, and some important implementation details, resulting in an algorithm that is practical for natural-language applications. The algorithm is part of Bolinas, a new software toolkit for HRG processing.