Parsing (State of the art)
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- Performance measure: PARSEVAL - the evalb program
- Training data: sections 2-22 of Wall Street Journal corpus
- Testing data: section 23 of Wall Street Journal corpus
| System name | Short description | Main publications | Software | Results (PARSEVAL) | Comments |
|---|---|---|---|---|---|
| Johnson & Charniak's Parser | Lexicalized N-Best PCFG + Discriminative re-reanking | Johnson and Charniak (2005) | download | 91.4% | works well also on Brown |
| Collins' Parser | Lexicalized PCFG | Collins (1999), Bikel (2004) | Dan Bikel's implementation | ??? | |
| Berkeley Parser | Automatically induced PCFG | Petrov, Barrett, Thibaux and Klein, ACL 2006 [1], Petrov and Klein, NAACL 2007 [2] | Berkeley Parser | 90.1% | works well also for Chinese and German |
Bikel, D. (2004). [http://www.cis.upenn.edu/~dbikel/papers/thesis.pdf On The Parameter Space of Generative Lexicalized
Statistical Parsing Models]. PhD Thesis, Computer and Information Science, University of Pennsylvania.
Collins, M. (1999). Head-driven Statistical Models for Natural Language Parsing. PhD Thesis, Computer and Information Science, University of Pennsylvania.
Johnson, M., and Charniak, E. (2005). Coarse-to-fine n-best parsing and MaxEnt discriminative reranking. Proceedings of the 43rd Annual Meeting of the ACL, pages 173–180, Ann Arbor, June 2005.