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.