Sample Selection for Statistical Parsing

  title={Sample Selection for Statistical Parsing},
  author={Rebecca Hwa},
  journal={Computational Linguistics},
Corpus-based statistical parsing relies on using large quantities of annotated text as training examples. Building this kind of resource is expensive and labor-intensive. This work proposes to use sample selection to find helpful training examples and reduce human effort spent on annotating less informative ones. We consider several criteria for predicting whether unlabeled data might be a helpful training example. Experiments are performed across two syntactic learning tasks and within the… CONTINUE READING
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