in history-based models ( Black et al. , 1993 ) , the probability estimate for each derivation decision di is conditioned on the previous derivation decisions d1 , ... , d , _ 1 , which is called the derivation history at step i .
towards historybased grammars using richer models for probabilistic parsing
E Black F Jelinek J Lafferty D Magerman R Mercer S Roukos
The probability of the input sentence is a constant across all the candidate derivations , so we only need to find the most probable derivation . in history-based models ( Black et al. , 1993 ) , the probability estimate for each derivation decision di is conditioned on the previous derivation decisions d1 , ... , d , _ 1 , which is called the derivation history at step i . This allows us to use the chain rule for conditional probabilities to derive the probability of the entire derivation as the multiplication of the probabilities for each of its decisions .
in history-based models ( @@CITATION ) , the probability estimate for each derivation decision di is conditioned on the previous derivation decisions d1 , ... , d , _ 1 , which is called the derivation history at step i .