As in previous work, we use a Goodman-transformed TAG as our proposal distribution (Goodman, 2003) that incorporates additional CFG rules to account for the possibility of backing off to the infinite base distribution P aux 0 , and use the parsing algorithm described by Shieber et al.
we present a Bayesian nonparametric model for estimating a probabilistic TAG from a parsed corpus, along with novel block sampling methods and approximation transformations for TAG that allow efficient parsing.