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

Reut Tsarfaty, Djamé Seddah, Yoav Goldberg, Sandra Kübler, Marie Candito, Jennifer Foster, Yannick Versley, Ines Rehbein, Lamia Tounsi

نتاج البحث: نتاج بحثي من مؤتمرمحاضرةمراجعة النظراء

ملخص

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.

اللغة الأصليةالإنجليزيّة
الصفحات1-12
عدد الصفحات12
حالة النشرنُشِر - 2010
منشور خارجيًانعم
الحدث1st Workshop on Statistical Parsing of Morphologically-Rich Languages, SPMRL 2010 - Los Angeles, الولايات المتّحدة
المدة: ٥ يونيو ٢٠١٠ → …

!!Conference

!!Conference1st Workshop on Statistical Parsing of Morphologically-Rich Languages, SPMRL 2010
الدولة/الإقليمالولايات المتّحدة
المدينةLos Angeles
المدة٥/٠٦/١٠ → …

ملاحظة ببليوغرافية

Publisher Copyright:
© 2010 Association for Computational Linguistics

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