Comparison of Turkish proposition banks by frame matching
Yükleniyor...
Dosyalar
Tarih
2018-12-06
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
IEEE
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
By indicating semantic relations between a predicate and its associated participants in a sentence and identifying the role-bearing constituents, SRL provides an extensive dataset to understand natural languages and to enhance several NLP applications such as information retrieval, machine translation, information extraction, and question answering. The availability of large resources and the development of statistical machine learning methods have increased the studies in the field of SRL. One of the widely-used semantic resources applied for multiple languages is PropBank. In this paper, PropBanks applied for Turkish are compared by checking semantic roles in the frame files of matched verb senses. As this integrated lexical resource for Turkish is aimed to be used in a multilingual resource along with English, creation of an inclusive lexical resource for Turkish is of great importance.
Açıklama
Anahtar Kelimeler
Turkish propbank, Learning systems, Machine translations, Multiple languages, Natural languages, Question answering, Semantic relations, Semantic resources, Statistical machine learning
Kaynak
2018 3rd International Conference on Computer Science and Engineering (UBMK)
WoS Q Değeri
N/A
Scopus Q Değeri
N/A
Cilt
Sayı
Künye
Ak, K., Bakay, O. & Yıldız, O. T. (2018). Comparison of turkish proposition banks by frame matching. Paper presented at the 2018 3rd International Conference on Computer Science and Engineering (UBMK), 352-356. doi:10.1109/UBMK.2018.8566426
