Probabilistic Context-Free Grammar Induction Based on Structural Zeros

We present a method for induction of concise and accurate probabilistic contextfree grammars for efficient use in early stages of a multi-stage parsing technique. The method is based on the use of statistical tests to determine if a non-terminal combination is unobserved due to sparse data or hard syntactic constraints. Experimental results show that, using this method, high accuracies can be achieved with a non-terminal set that is orders of magnitude smaller than in typically induced probabilistic context-free grammars, leading to substantial speed-ups in parsing. The approach is further used in combination with an existing reranker to provide competitive WSJ parsing results.