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Parsing Noun Phrases in the Penn Treebank

What it is about

The Penn Treebank does not mark the internal structure of noun phrases, so statistical parsers cannot learn it. The authors annotate NP structure by hand for the whole Wall Street Journal section of the treebank, and the inter-annotator agreement shows that the task is feasible. The Collins parser recovers NP structure worse than its overall performance, up to 5.69 F-score points below a rule baseline, and the authors trace this to missing lexical information. A supervised NP bracketing model with lexical and other features reaches 93.8% F-score on simple NPs and 89.14% on the harder, longer NPs, and as a post-processor it raises the parser's NP brackets by 9.04 points.

Ideas

For Mova

The NP logic belongs in en/src/parse.rs (features) and in a post-processor next to it; the lexicon is en/seeds/nominal. The chapter that the ideas touch is 22. Phrases: noun, adjective, adverb and prepositional phrases. Measure first: UAS on the NP-internal arcs of EWT test, reported separately from the overall LAS.

Topics: Treebanks

Cite

The paper itself, not this card. BibTeX from the library's record of the work. DOI 10.1162/coli_a_00076

@article{vadas2011parsing,
  title = {{Parsing Noun Phrases in the Penn Treebank}},
  author = {Vadas, David and Curran, James R.},
  journal = {Computational Linguistics},
  year = {2011},
  doi = {10.1162/coli\_a\_00076},
  url = {https://doi.org/10.1162/coli_a_00076}
}

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