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Long-distance dependency resolution in automatically acquired wide-coverage PCFG-based LFG approximations

Cahill, Aoife and Burke, Michael and O'Donovan, Ruth and van Genabith, Josef and Way, Andy (2004) Long-distance dependency resolution in automatically acquired wide-coverage PCFG-based LFG approximations. In: ACL 2004 - 42nd Annual Meeting of the Association for Computational Linguistics, 21-26 July 2004, Barcelona, Spain.

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Abstract

This paper shows how finite approximations of long distance dependency (LDD) resolution can be obtained automatically for wide-coverage, robust, probabilistic Lexical-Functional Grammar (LFG) resources acquired from treebanks. We extract LFG subcategorisation frames and paths linking LDD reentrancies from f-structures generated automatically for the Penn-II treebank trees and use them in an LDD resolution algorithm to parse new text. Unlike (Collins, 1999; Johnson, 2002), in our approach resolution of LDDs is done at f-structure (attribute-value structure representations of basic predicate-argument or dependency structure) without empty productions, traces and coindexation in CFG parse trees. Currently our best automatically induced grammars achieve 80.97% f-score for fstructures parsing section 23 of the WSJ part of the Penn-II treebank and evaluating against the DCU 1051 and 80.24% against the PARC 700 Dependency Bank (King et al., 2003), performing at the same or a slightly better level than state-of-the-art hand-crafted grammars (Kaplan et al., 2004).

Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Uncontrolled Keywords:lexical functional grammar;
Subjects:Computer Science > Machine translating
DCU Faculties and Centres:Research Initiatives and Centres > National Centre for Language Technology (NCLT)
DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Publisher:Association for Computational Linguistics
Official URL:http://www.aclweb.org/anthology/P/P04/
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:Enterprise Ireland, EI SC/2001/186, Irish Research Council for Science Engineering and Technology
ID Code:15303
Deposited On:15 Mar 2010 11:27 by DORAS Administrator. Last Modified 28 Apr 2010 11:28

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