Multiword Expressions in Statistical Dependency Parsing

Gülşen Eryiğit, Tugay İlbay, Ozan Arkan Can

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38 Atıf (Scopus)

Özet

In this paper, we investigated the impact of extracting different types of multiword expressions (MWEs) in improving the accuracy of a data-driven dependency parser for a morphologically rich language (Turkish). We showed that in the training stage, the unification of MWEs of a certain type, namely compound verb and noun formations, has a negative effect on parsing accuracy by increasing the lexical sparsity. Our results gave a statistically significant improvement by using a variant of the treebank excluding this MWE type in the training stage. Our extrinsic evaluation of an ideal MWE recognizer (for only extracting MWEs of type named entities, duplications, numbers, dates and some predefined list of compound prepositions) showed that the preprocessing of the test data would improve the labeled parsing accuracy by 1.5%.

Orijinal dilİngilizce
Ana bilgisayar yayını başlığı2nd Workshop on Statistical Parsing of Morphologically Rich Languages, SPMRL 2011 - collocate with the International Workshop on Parsing Technologies, IWPT 2011 - Proceedings
EditörlerDjame Seddah, Reut Tsarfaty, Jennifer Foster
YayınlayanAssociation for Computational Linguistics (ACL)
Sayfalar45-55
Sayfa sayısı11
ISBN (Elektronik)9781932432732
Yayın durumuYayınlandı - 2011
Etkinlik2nd Workshop on Statistical Parsing of Morphologically Rich Languages, SPMRL 2011 - Dublin, Ireland
Süre: 6 Eki 2011 → …

Yayın serisi

Adı2nd Workshop on Statistical Parsing of Morphologically Rich Languages, SPMRL 2011 - collocate with the International Workshop on Parsing Technologies, IWPT 2011 - Proceedings

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???event.eventtypes.event.conference???2nd Workshop on Statistical Parsing of Morphologically Rich Languages, SPMRL 2011
Ülke/BölgeIreland
ŞehirDublin
Periyot6/10/11 → …

Bibliyografik not

Publisher Copyright:
© 2011 Association for Computational Linguistics

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