Tounsi, Lamia, Attia, Mohammed and van Genabith, Josef ORCID: 0000-0003-1322-7944 (2009) Automatic treebank-based acquisition of Arabic LFG dependency structures. In: EACL 2009 Workshop on Computational Approaches to Semitic Languages, 31 March 2009, Athens, Greece.
Abstract
A number of papers have reported on methods for the automatic acquisition of large-scale, probabilistic LFG-based grammatical resources from treebanks for English (Cahill and al., 2002), (Cahill and al., 2004), German (Cahill and al., 2003), Chinese (Burke, 2004), (Guo and al.,
2007), Spanish (O’Donovan, 2004), (Chrupala and van Genabith, 2006) and French (Schluter and van Genabith, 2008). Here, we extend the LFG grammar acquisition approach to Arabic and the Penn Arabic Treebank (ATB) (Maamouri and
Bies, 2004), adapting and extending the methodology
of (Cahill and al., 2004) originally developed for English. Arabic is challenging because of its morphological richness and syntactic complexity.
Currently 98% of ATB trees (without FRAG and X) produce a covering and connected f-structure.
We conduct a qualitative evaluation of our annotation
against a gold standard and achieve an f-score of 95%.
Metadata
Item Type: | Conference or Workshop Item (Paper) |
---|---|
Event Type: | Workshop |
Refereed: | Yes |
Uncontrolled Keywords: | lexical functional grammar; Arabic; treebank; |
Subjects: | Computer Science > Machine translating |
DCU Faculties and Centres: | Research Institutes 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/W/W09/W09-0806.pdf |
Copyright Information: | ©2009 Association for Computational Linguistics |
Use License: | This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License |
Funders: | Science Foundation Ireland, SFI 04/IN/I527 |
ID Code: | 15148 |
Deposited On: | 12 Feb 2010 14:38 by DORAS Administrator . Last Modified 21 Jan 2022 16:31 |
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