K-best Iterative Viterbi Parsing

This paper presents an efficient and optimal parsing algorithm for probabilistic context-free grammars (PCFGs). To achieve faster parsing, our proposal employs a pruning technique to reduce unnecessary edges in the search space. The key is to repetitively conduct Viterbi inside and outside parsing, while gradually expanding the search space to efficiently compute heuristic bounds used for pruning. This paper also shows how to extend this algorithm to extract K-best Viterbi trees. Our experimental results show that the proposed algorithm is faster than the standard CKY parsing algorithm. Moreover, its K-best version is much faster than the Lazy K-best algorithm when K is small.