Because each rule r consists of a target tree fragment frag and a source string str in the model , we follow Cohn and Blunsom ( 2009 ) and decompose the prior probability P0 ( r | N ) into two factors as follows :
a bayesian model of syntaxdirected tree to string grammar induction
Trevor Cohn Phil Blunsom
The base distribution P0 ( r | N ) is designed to assign prior probabilities to the STSG production rules . Because each rule r consists of a target tree fragment frag and a source string str in the model , we follow Cohn and Blunsom ( 2009 ) and decompose the prior probability P0 ( r | N ) into two factors as follows : where P ( frag | N ) is the probability of producing the target tree fragment frag .
Because each rule r consists of a target tree fragment frag and a source string str in the model , we follow @@CITATION and decompose the prior probability P0 ( r | N ) into two factors as follows :