Probabilistic Parsing Using Left Corner Language Models
<|reference_start|>Probabilistic Parsing Using Left Corner Language Models: We introduce a novel parser based on a probabilistic version of a left-corner parser. The left-corner strategy is attractive because rule probabilities can be conditioned on both top-down goals and bottom-up derivations. We develop the underlying theory and explain how a grammar can be induced from analyzed data. We show that the left-corner approach provides an advantage over simple top-down probabilistic context-free grammars in parsing the Wall Street Journal using a grammar induced from the Penn Treebank. We also conclude that the Penn Treebank provides a fairly weak testbed due to the flatness of its bracketings and to the obvious overgeneration and undergeneration of its induced grammar.<|reference_end|>
@article{manning1997probabilistic,
    title={Probabilistic Parsing Using Left Corner Language Models},
    author={Christopher D. Manning (University of Sydney) and Bob Carpenter
  (Lucent Technologies Bell Labs)},
    journal={Proceedings of the Fifth International Workshop on Parsing
  Technologies, MIT, Boston MA, 1997},
    year={1997},
    archivePrefix={arXiv},
    eprint={cmp-lg/9711003},
    primaryClass={cmp-lg cs.CL}
}