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Closing the gap between stochastic and rule-based LFG grammars

Hautli, Annette, Cetinoglu, Ozlem and van Genabith, Josef orcid logoORCID: 0000-0003-1322-7944 (2010) Closing the gap between stochastic and rule-based LFG grammars. In: the LFG10 Conference, 18-20 July 2010, Ottowa, Canada.

Abstract
Developing large-scale deep grammars in a constraint-based framework such as Lexical Functional Grammar (LFG) is time-consuming and requires significant linguistic insight. Recently, treebank-based constraint-grammar acquisition approaches have been developed as an alternative to hand-crafting such resources. While treebank-based approaches are wide coverage and robust and achieve competitive evaluation results for many languages, the granularity of the linguistic analyses provided by treebank-based resources tends to be less fine-grained than what is offered by state-of-the-art handcrafted grammars. This paper presents an approach to extend the English DCU LFG annotation algorithm with more detailed f-structure information to provide probabilistic treebank-based LFG grammars with rich feature information comparable to that implemented by the hand-crafted English XLE grammar, while maintaining the robustness and the coverage of treebankbased stochastic grammars.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Uncontrolled Keywords:Lexical Functional Grammar; LFG
Subjects:Computer Science > Machine translating
DCU Faculties and Centres:Research Initiatives and Centres > Centre for Next Generation Localisation (CNGL)
Research Initiatives and Centres > National Centre for Language Technology (NCLT)
Published in: Proceedings of LFG10. . CSLI Publications.
Publisher:CSLI Publications
Official URL:http://cslipublications.stanford.edu/LFG/15/abstra...
Copyright Information:© 2010 CSLI Publications
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:16017
Deposited On:19 May 2011 09:40 by Shane Harper . Last Modified 20 Jan 2022 16:04
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