Sample Selection for Statistical Grammar Induction

@inproceedings{Hwa2000SampleSF,
  title={Sample Selection for Statistical Grammar Induction},
  author={Rebecca Hwa},
  booktitle={EMNLP},
  year={2000}
}
Corpus-based grz.mmar induction relies on using many hand-parsed sentences as training examples. However, the construction of a training corpus with detailed syntactic analysis for every sentence is a labor-intensive task. We propose to use sample selection methods to minimize the amount of annotation needed in the training data, thereby reducing the workload of the human annotators. This paper shows that the amount of annotated training data can be reduced by 36% without degrading the quality… CONTINUE READING
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