We describe a generative model for nonprojective dependency parsing based on a simplified version of a transition system that has recently appeared in the literature. We then develop a dynamic programming parsing algorithm for our model, and derive an insideoutside algorithm that can be used for unsupervised learning of non-projective dependency trees.
A generative transition-based parsing model for non-projective parsing is proposed in REF , along with a dynamic program for inference.
Exact Inference for Generative Probabilistic Non-Projective Dependency Parsing
EMNLP
Computer Science