Exploiting Diversity in Natural Language Processing: Combining Parsers
arXiv:cs/0006003
Abstract
Three state-of-the-art statistical parsers are combined to produce more accurate parses, as well as new bounds on achievable Treebank parsing accuracy. Two general approaches are presented and two combination techniques are described for each approach. Both parametric and non-parametric models are explored. The resulting parsers surpass the best previously published performance results for the Penn Treebank.
8 pages
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- Diversity in Spectral Learning for Natural Language Parsing
- Probabilistic top-down parsing and language modeling