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Grammatical feature data-oriented parsing

Finn, Regina (2007) Grammatical feature data-oriented parsing. Master of Science thesis, Dublin City University.

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Abstract

LFG-DOP is a powerful, hybrid model of language processing where the tree representations of Data-Oriented Parsing (DOP) are augmented with the functional representations of Lexical Functional Grammar (LFG). The result is a robust parsing model which generates linguistically informed output. However, difficulties arise in the accurate implementation of fragmentation and sampling in this model. Due to these unresolved issues, there is currently no satisfactory implementation of the LFG-DOP model. In this thesis, we propose a backing-off to Grammatical Feature-DOP (GF-DOP). The GF-DOP model differs from Tree-DOP and LFG-DOP in that the trees are annotated with selected features extracted from the f-structure, rather than explicitly linked to corresponding f-structure units. In this way, we rnake use of the irlformation available to us in the f-structure, while avoiding the problems inherent in the implementation of LFG-DOP. We aim to improve the quality of the parses generated by modeling additional functional and feature information. Experiments on the HomeCentre corpus have shown this model to be a valuable middleground between the two alternative models. GF-DOP has been shown to outperform the Tree-DOP model, as a result of its ability to identify and make use of grammatical features, while maintaining the integrity of the probability model.

Item Type:Thesis (Master of Science)
Date of Award:2007
Refereed:No
Supervisor(s):Way, Andy and Hearne, Mary
Uncontrolled Keywords:Data-Oriented Parsing; DOP; Lexical Functional Grammar; LFG; Grammatical Feature; GF-DOP
Subjects:Computer Science > Machine translating
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 3.0 License. View License
ID Code:17009
Deposited On:15 May 2012 12:08 by Fran Callaghan. Last Modified 15 May 2012 12:08

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