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

פרסום מחקרי: תוצר מחקר מכנסהרצאהביקורת עמיתים

תקציר

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.

שפה מקוריתאנגלית
עמודים1-12
מספר עמודים12
סטטוס פרסוםפורסם - 2010
פורסם באופן חיצוניכן
אירוע1st Workshop on Statistical Parsing of Morphologically-Rich Languages, SPMRL 2010 - Los Angeles, ארצות הברית
משך הזמן: 5 יוני 2010 → …

כנס

כנס1st Workshop on Statistical Parsing of Morphologically-Rich Languages, SPMRL 2010
מדינה/אזורארצות הברית
עירLos Angeles
תקופה5/06/10 → …

הערה ביבליוגרפית

Publisher Copyright:
© 2010 Association for Computational Linguistics

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