Moreover , in order to determine whether the performances of the predictive criteria are consistent across different learning models within the same domain , we have performed the study on two parsing models : one based on a context-free variant of tree-adjoining grammars ( Joshi , Levy , and Takahashi 1975 ) , the Probabilistic Lexicalized Tree Insertion Grammar ( PLTIG ) formalism ( Schabes and Waters 1993 ; Hwa 1998 ) , and Collins 's Model 2 parser ( 1997 ) .
stochastic lexicalized contextfree grammar
Yves Schabes Richard Waters
In this section , we investigate whether these observations hold true for training statistical parsing models as well . Moreover , in order to determine whether the performances of the predictive criteria are consistent across different learning models within the same domain , we have performed the study on two parsing models : one based on a context-free variant of tree-adjoining grammars ( Joshi , Levy , and Takahashi 1975 ) , the Probabilistic Lexicalized Tree Insertion Grammar ( PLTIG ) formalism ( Schabes and Waters 1993 ; Hwa 1998 ) , and Collins 's Model 2 parser ( 1997 ) . Although both models are lexicalized , statistical parsers , their learning algorithms are different .
Moreover , in order to determine whether the performances of the predictive criteria are consistent across different learning models within the same domain , we have performed the study on two parsing models : one based on a context-free variant of tree-adjoining grammars ( Joshi , Levy , and Takahashi 1975 ) , the Probabilistic Lexicalized Tree Insertion Grammar ( PLTIG ) formalism ( @@CITATION ; Hwa 1998 ) , and Collins 's Model 2 parser ( 1997 ) .