Type-based MCMC for Sampling Tree Fragments from Forests

This paper applies type-based Markov Chain Monte Carlo (MCMC) algorithms to the problem of learning Synchronous Context-Free Grammar (SCFG) rules from a forest that represents all possible rules consistent with a fixed word alignment. While type-based MCMC has been shown to be effective in a number of NLP applications, our setting, where the tree structure… CONTINUE READING