2026-09-19T13:57:47Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/44091 2023-07-11 col_2142_5131 col_2142_10761 com_2142_5130 com_2142_10755 com_2142_234

Girju, Roxana Lundgren, David 2013-05-24T21:50:24Z 2013-05-24T21:50:24Z 2013-05 2013-05-24T21:50:24Z 2013-05 In this thesis, I examine the impact of morphological features on semantic role labeling (SRL) in Modern Standard Arabic. This study provides the first rigorous examination of the effect of individual morphological attributes on the automatic classification of predicate-argument roles in Arabic. I obtain a classification accuracy comparable to the best-published previous results using fewer features and a linear kernel SVM. This provides evidence that there is a strong morpho-semantic interaction in Arabic and that careful, language-dependent feature engineering may provide substantial improvements to morphologically rich languages. I demonstrate that the incorporation of rich-morphological features substantially outperform the established lexico-syntactic featuresets of standard SRL systems. A principled feature selection algorithm for SRL is also introduced that significantly decreases generalization error, leading to state-of-the-art argument role classification results. Item withdrawn by Mark Zulauf (zulauf@illinois.edu) on 2013-04-22T12:54:00Z Item was in collections: University of Illinois Theses & Dissertations (ID: 1) No. of bitstreams: 1 Lundgren_David.pdf: 327310 bytes, checksum: f18c382ebe9dd0b7e3a55e36f73ca175 (MD5) Made available in DSpace on 2013-05-24T21:50:24Z (GMT). No. of bitstreams: 2 David_Lundgren.pdf: 326519 bytes, checksum: 08c139b87ffd96d39d0cb6a91724e0fc (MD5) license.txt: 4064 bytes, checksum: 0dbe750d773dcc3519c0e1ef399e9e7c (MD5) http://hdl.handle.net/2142/44091 en Copyright 2013 David Lundgren semantic role labeling (SRL) Arabic morphology semantics Semantic role labeling using rich morphological features text Computer Science 1434 Computer Science 0112 University of Illinois at Urbana-Champaign Thesis M.S. MS:Computer Science -UIUC 10KS0112MS