Rebecca Nesson


Complexity, Parsing, and Factorization of Tree-Local Multi-Component Tree-Adjoining Grammar
Rebecca Nesson | Giorgio Satta | Stuart M. Shieber
Computational Linguistics, Volume 36, Issue 3 - September 2010


Efficiently Parsable Extensions to Tree-Local Multicomponent TAG
Rebecca Nesson | Stuart Shieber
Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics


Optimal k-arization of Synchronous Tree-Adjoining Grammar
Rebecca Nesson | Giorgio Satta | Stuart M. Shieber
Proceedings of ACL-08: HLT

Synchronous Vector TAG for Syntax and Semantics: Control Verbs, Relative Clauses, and Inverse Linking
Rebecca Nesson | Stuart Shieber
Proceedings of the Ninth International Workshop on Tree Adjoining Grammar and Related Frameworks (TAG+9)


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Extraction Phenomena in Synchronous TAG Syntax and Semantics
Rebecca Nesson | Stuart M. Shieber
Proceedings of SSST, NAACL-HLT 2007 / AMTA Workshop on Syntax and Structure in Statistical Translation


Induction of Probabilistic Synchronous Tree-Insertion Grammars for Machine Translation
Rebecca Nesson | Stuart Shieber | Alexander Rush
Proceedings of the 7th Conference of the Association for Machine Translation in the Americas: Technical Papers

The more expressive and flexible a base formalism for machine translation is, the less efficient parsing of it will be. However, even among formalisms with the same parse complexity, some formalisms better realize the desired characteristics for machine translation formalisms than others. We introduce a particular formalism, probabilistic synchronous tree-insertion grammar (PSTIG) that we argue satisfies the desiderata optimally within the class of formalisms that can be parsed no less efficiently than context-free grammars and demonstrate that it outperforms state-of-the-art word-based and phrase-based finite-state translation models on training and test data taken from the EuroParl corpus (Koehn, 2005). We then argue that a higher level of translation quality can be achieved by hybridizing our in- duced model with elementary structures produced using supervised techniques such as those of Groves et al. (2004).