We present an empirical study of the applicability of Probabilistic Lexicalized Tree Insertion Grammars (PLTIG), a lexicalized counterpart to Probabilistic Context-Free Grammars (...
The Context-Free backbone of some natural language analyzers produces all possible CF parses as some kind of shared forest, from which a single tree is to be chosen by a disambigu...
Current parsing models are not immediately applicable for languages that exhibit strong interaction between morphology and syntax, e.g., Modern Hebrew (MH), Arabic and other Semit...
We explore a new Bayesian model for probabilistic grammars, a family of distributions over discrete structures that includes hidden Markov models and probabilistic context-free gr...
Adaptor grammars extend probabilistic context-free grammars to define prior distributions over trees with "rich get richer" dynamics. Inference for adaptor grammars seek...