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The Penn Treebank: Annotating Predicate Argument Structure

What it is about

The paper describes a second annotation scheme for the Penn Treebank, written to make predicate-argument structure recoverable from the trees. It makes related phenomena consistent, adds co-indexed null elements for wh-movement, passives and infinitival subjects, gives a mechanism for discontinuous constituents, and tags arguments and adjuncts with function labels such as -SBJ, -TMP and -PRD. Small clauses map to a single predication, so that "consider Kris a fool" yields one predicate. The authors report an eight-month effort by about ten annotators to write the stylebook, and they plan 10% overlapped material to measure consistency. The paper gives no accuracy figures; its value is the scheme and the stated goal of evaluating parsers on predicate-argument structure.

Ideas

For Mova

The code is en/src/convert.rs, treebanks/en/ and annot. The chapters are 23. Complementation (small clauses and control), 25-relative-clauses.md (wh-traces) and 28-voice-and-passive.md (passive subjects). Measure first: how many gold relations in the PTB conversion depend on a trace, since that count sets the cost of recovering them.

Topics: Treebanks · Semantic role labeling

Cite

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

@inproceedings{marcus1994penn,
  title = {{The Penn Treebank: Annotating Predicate Argument Structure}},
  author = {Marcus, Mitchell and Kim, Grace and Marcinkiewicz, Mary Ann and MacIntyre, Robert and Bies, Ann and Ferguson, Mark and Katz, Karen and Schasberger, Britta},
  booktitle = {Human Language Technology: Proceedings of a Workshop held at Plainsboro, New Jersey, March 8-11, 1994},
  year = {1994},
  url = {https://aclanthology.org/H94-1020/}
}

References

11 references, 1 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

  1. Black, E., Abney, S., Flickenger, F., Grishman, R., Harrison, P., Hindle, D., Ingria, R., Jelinek, F., Klavans, J., Liberman, M., Marcus, M., Roukos, S., Santorini, B., and Strzalkowski, T., 1991. A procedure for quantitatively comparing the syntactic coverage of English grammars. In Proceedings of the Fourth DARPA Speech and Natural Language Workshop, February 1991. find
  2. Black, E., Jelinek, F., Lafferty, J., Magerman, D.M., Mercer, R., and Roukos, S. 1992. Towards history-based grammars: Using Richer Models for Probabilistic parsing. In Proceedings of the $1th Annual Meeting of the Association for Computational Linguistics. find
  3. Brill, E., Marcus, M., 1992. Automatically acquiring phrase structure using distributional analysis. In Proceedings of the DARPA Speech and Natural Language Workshop, February 199~. find
  4. Brill, E., 1993. Automatic grammar induction and parsing free text: a transformation-based approach. In Proceedings of the 31th Annual Meeting of the Association for Computational Linguistics. find
  5. Francis, W., 1964. A standard sample of present-day English for use with digital computers. Report to the U.S Office of Education on Cooperative Research Project No. E-OOZ Brown University, Providence. find
  6. Francis, W. and Ku~era, H., 1982. Frequency analysis of English usage. Lexicon and grammar. Houghton Mifflin, Boston. The computational analysis of English. A corpus-based approach. Longman, London. find
  7. Garside, R., Leech, G., and Sampson, G., 1987. find
  8. Hindle, D., and Rooth, M., 1993. Structural Ambiguity and Lexical Relations. Computational Linguistics, Vol 19. find
  9. D. Magerman and M. Marcus, 1991. P E A R L - - A Probabilistic Chart Parser, In Proceedings, Fifth Conference of the European Chapter off the Association for Computational Linguistics (EACL), Berlin, April 1991. find
  10. Marcus, M., Santorini, B., Marcinkiewicz, M.A., 1993. Building a large annotated corpus of English: the Penn Treebank. Computational Linguistics, Vol 19. find our card
  11. Quirk, R., Greenbanm, S., Leech, G., and Svaxtvik, J., 1985. A comprehensive grammar of the English language, Longman, London. find

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