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Statistical Parsing of Morphologically Rich Languages (SPMRL) What, How and Whither

Authors :
Tsarfaty, Reut
Seddah, Djamé
Goldberg, Yoav
Kübler, Sandra
Candito, Marie
Foster, Jennifer
Versley, Yannick
Rehbein, Ines
Tounsi, Lamia
Uppsala University
Analyse Linguistique Profonde à Grande Echelle
Large-scale deep linguistic processing (ALPAGE)
Inria Paris-Rocquencourt
Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université Paris Diderot - Paris 7 (UPD7)
Ben-Gurion University of the Negev (BGU)
Indian Institute of Science [Bangalore] (IISc Bangalore)
Emmy Noether Project (SFB 833)
Eberhard Karls Universität Tübingen = Eberhard Karls University of Tuebingen
National Centre for Language Technology (NCLT)
Dublin City University [Dublin] (DCU)
Allgemeine Linguistik Computational Linguistics and phonetics (Allgemeine Linguistik)
Saarland University [Saarbrücken]
Source :
Proceedings of the NAACL HLT 2010 First Workshop on Statistical Parsing of Morphologically-Rich Languages, Proceedings of the NAACL HLT 2010 First Workshop on Statistical Parsing of Morphologically-Rich Languages, 2010, Los Angeles, United States. pp.1--12
Publication Year :
2010
Publisher :
HAL CCSD, 2010.

Abstract

The term Morphologically Rich Languages (MRLs) refers to languages in which significant information concerning syntactic units and relations is expressed at word-level. There is ample evidence that the application of readily available statistical parsing models to such languages is susceptible to serious performance degradation. The first workshop on statistical parsing of MRLs hosts a variety of contributions which show that despite language-specific idiosyncrasies, the problems associated with parsing MRLs cut across languages and parsing frameworks. In this paper we review the current state-of-affairs with respect to parsing MRLs and point out central challenges. We synthesize the contributions of researchers working on parsing Arabic, Basque, French, German, Hebrew, Hindi and Korean to point out shared solutions across languages. The overarching analysis suggests itself as a source of directions for future investigations.

Details

Language :
English
Database :
OpenAIRE
Journal :
Proceedings of the NAACL HLT 2010 First Workshop on Statistical Parsing of Morphologically-Rich Languages, Proceedings of the NAACL HLT 2010 First Workshop on Statistical Parsing of Morphologically-Rich Languages, 2010, Los Angeles, United States. pp.1--12
Accession number :
edsair.dedup.wf.001..563b00a58a9dcf17483d36d97db0fe26