Exploring Higher Order Dependency Parsers

• Thesis title in English: Exploring Higher Order Dependency Parsers
• Key words: higher order, dependency parsing, non-projectivity
• English key words: higher order, dependency parsing, non-projectivity
• Academic year of topic announcement: 2010/2011
• Thesis type: diploma thesis
• Thesis language: angličtina
• Department: Institute of Formal and Applied Linguistics (32-UFAL)
• Supervisor: doc. RNDr. Daniel Zeman, Ph.D.
• Author: hidden - assigned and confirmed by the Study Dept.
• Date of registration: 12.11.2010
• Date of assignment: 12.11.2010
• Confirmed by Study dept. on: 29.04.2013
• Date and time of defence: 06.09.2011 00:00
• Date of electronic submission: 04.08.2011
• Date of submission of printed version: 04.08.2011
• Date of proceeded defence: 06.09.2011
• Opponents: RNDr. David Mareček, Ph.D.

Guidelines

Most of the recent efficient algorithms for dependency parsing work by factoring the dependency trees. In most of these approaches, the parser loses much of the contextual information during the process of factorization. There have been approaches to build higher order dependency parsers - second order, Carreras 2007 and third order - Koo and Collins 2010. In the thesis, the approach by Koo and Collins should be further exploited in one or more ways. Possible directions of further exploitation include but are not limited to: investigating possibilities of extension of the approach to non-projective parsing; integrating labeled parsing; joining word-senses during the parsing phase (Eisner 2000).

References

Xavier Carreras. 2007. Experiments with a Higher- Order Projective Dependency Parser. In Proceedings of the CoNLL Shared Task Session of EMNLP- CoNLL, pages 957-961. Association for Computational Linguistics.

Terry Koo and Michael Collins 2010, EFFICIENT THIRD-ORDER DEPENDENCY PARSERS. Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics, Uppsala, Sweden.

Jason Eisner. 2000. Bilexical Grammars and Their Cubic-Time Parsing Algorithms. In Harry Bunt and Anton Nijholt, editors, Advances in Probabilistic and Other Parsing Technologies, pages 29-62. Kluwer Academic Publishers.