A log-linear model with an n-gram reference distribution for accurate HPSG parsing

@inproceedings{Ninomiya2007ALM,
  title={A log-linear model with an n-gram reference distribution for accurate HPSG parsing},
  author={Takashi Ninomiya and Takuya Matsuzaki and Yusuke Miyao and Jun'ichi Tsujii},
  booktitle={IWPT},
  year={2007}
}
This paper describes a log-linear model with an n-gram reference distribution for accurate probabilistic HPSG parsing. In the model, the n-gram reference distribution is simply defined as the product of the probabilities of selecting lexical entries, which are provided by the discriminative method with machine learning features of word and POS n-gram as defined in the CCG/HPSG/CDG supertagging. Recently, supertagging becomes well known to drastically improve the parsing accuracy and speed, but… CONTINUE READING
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