We discuss the relevance of k-best parsing to recent applications in natural language processing, and develop efficient algorithms for k-best trees in the framework of hypergraph parsing. To demonstrate the efficiency, scalability and accuracy of these algorithms, we present experiments on Bikel's implementation of Collins' lexicalized PCFG model, and on Chiang's CFG-based decoder for hierarchical phrase-based translation. We show in particular how the improved output of our algorithms has the potential to improve results from parse reranking systems and other applications.
In terms of k-best parsing, REF proposed an efficient algorithm which is similar to the k-best Viterbi A* algorithm presented in this paper.
Better K-Best Parsing
International Workshop On Parsing Technology
Computer Science