Dependency Parsing with Dynamic Bayesian Network
<|reference_start|>Dependency Parsing with Dynamic Bayesian Network: Exact parsing with finite state automata is deemed inappropriate because of the unbounded non-locality languages overwhelmingly exhibit. We propose a way to structure the parsing task in order to make it amenable to local classification methods. This allows us to build a Dynamic Bayesian Network which uncovers the syntactic dependency structure of English sentences. Experiments with the Wall Street Journal demonstrate that the model successfully learns from labeled data.<|reference_end|>
@article{savova2007dependency,
    title={Dependency Parsing with Dynamic Bayesian Network},
    author={Virginia Savova and Leonid Peshkin},
    journal={In proceedings of American Association for Artificial Intelligence
  AAAI 2005},
    year={2007},
    archivePrefix={arXiv},
    eprint={cs/0703135},
    primaryClass={cs.CL cs.AI}
}