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Statistical Parsing of Morphologically Rich Languages (SPMRL) What, How and Whither
- 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.
- Subjects :
- hindi
german
[INFO.INFO-TT]Computer Science [cs]/Document and Text Processing
arabic
hebrew
french
Computational linguistics
Linguistics
statistical parsing
basque
morphologically rich languages
ComputingMilieux_MISCELLANEOUS
[INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]
Subjects
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