A Trellis-based algorithm for estimating the parameters of a hidden stochastic context-free grammar
HLT '91 Proceedings of the workshop on Speech and Natural Language
Generalized probabilistic LR parsing of natural language (Corpora) with unification-based grammars
Computational Linguistics - Special issue on using large corpora: I
Parsing the Wall Street Journal with the inside-outside algorithm
EACL '93 Proceedings of the sixth conference on European chapter of the Association for Computational Linguistics
| Hi-index | 0.00 |
A Probabilistic Recursive Transition Network is an elevated version of a Recursive Transition Network used to model and process context-free languages in stochastic parameters. We present a re-estimation algorithm for training probabilistic parameters, and show how efficiently it can be implemented using charts. The complexity of the Outside algorithm we present is O(N4G3) where N is the input size and G is the number of states. This complexity can be significantly overcome when the redundant computations are avoided. Experiments on the Penn tree corpus show that re-estimation can be done more efficiently with charts.