Latent-variable PCFGs: Background and applications

Abstract

Latent-variable probabilistic context-free grammars are latent-variable models that are based on context-free grammars. Non-terminals are associated with latent states that provide contextual information during the top-down rewriting process of the grammar. We survey a few of the techniques used to estimate such grammars and to parse text with them. We also give an overview of what the latent states represent for English Penn treebank parsing, and provide an overview of extensions and related models to these grammars.