DocumentCode :
2352348
Title :
Exploring Various Features in Semantic Role Labeling
Author :
Hongling Wang ; Guodong Zhou ; Qiaoming Zhu ; Peide Qian
Author_Institution :
Sch. of Comput. Sci. & Technol., Soochow Univ., Suzhou
fYear :
2008
fDate :
23-25 July 2008
Firstpage :
3
Lastpage :
8
Abstract :
This paper explores the contributions of various features in semantic role labeling. Moreover, an optimal set of features is selected using a greedy strategy. Finally, an effective headword-driven pruning algorithm is proposed to filter out irrelavant instances. Evaluation on the CoNLL´2005 SRL benchmark corpus shows that our method achieved comparable performance with the best-reported ones on a single automatic parse tree.
Keywords :
grammars; greedy algorithms; programming language semantics; greedy strategy; headword-driven pruning algorithm; semantic role labeling; single automatic parse tree; Computer science; Filters; Gold; Information processing; Information technology; Labeling; Magnetic heads; Support vector machine classification; Support vector machines; System performance; Semantic Role Labeling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Language Processing and Web Information Technology, 2008. ALPIT '08. International Conference on
Conference_Location :
Dalian Liaoning
Print_ISBN :
978-0-7695-3273-8
Type :
conf
DOI :
10.1109/ALPIT.2008.74
Filename :
4584332
Link To Document :
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