WordNet and wikipedia connection in Turkish WordNet KeNet

Name: WordNet and wikipedia connection in Turkish WordNet KeNet
Author: Doğan, M., Oksal, C., Yenice, A. B., Beyhan, F., Yeniterzi, R., Yıldız, Olcay Taner

İsim	WordNet and wikipedia connection in Turkish WordNet KeNet
Yazar	Doğan, M., Oksal, C., Yenice, A. B., Beyhan, F., Yeniterzi, R., Yıldız, Olcay Taner
Basım Tarihi:	2022
Basım Yeri	- European Language Resources Association (ELRA)
Konu	Turkish, Wikipedia, WordNet
Tür	Belge
Dil	İngilizce
Dijital	Evet
Yazma	Hayır
Kütüphane:	Özyeğin Üniversitesi
Demirbaş Numarası	979-109554692-4
Kayıt Numarası	92853a5c-6b81-498d-ad6d-73fed18f18e8
Lokasyon	Computer Science
Tarih	2022
Örnek Metin	This paper aims to present WordNet and Wikipedia connection by linking synsets from Turkish WordNet KeNet with Wikipedia and thus, provide a better machine-readable dictionary to create an NLP model with rich data. For this purpose, manual mapping between two resources is realized and 11,478 synsets are linked to Wikipedia. In addition to this, automatic linking approaches are utilized to analyze possible connection suggestions. Baseline Approach and ElasticSearch Based Approach help identify the potential human annotation errors and analyze the effectiveness of these approaches in linking. Adopting both manual and automatic mapping provides us with an encompassing resource of WordNet and Wikipedia connections.

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Özyeğin Üniversitesi

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WordNet and wikipedia connection in Turkish WordNet KeNet

Yazar Doğan, M., Oksal, C., Yenice, A. B., Beyhan, F., Yeniterzi, R., Yıldız, Olcay Taner

Basım Tarihi 2022

Basım Yeri - European Language Resources Association (ELRA)

Konu Turkish, Wikipedia, WordNet

Tür Belge

Dil İngilizce

Dijital Evet

Yazma Hayır

Kütüphane Özyeğin Üniversitesi

Demirbaş Numarası 979-109554692-4

Kayıt Numarası 92853a5c-6b81-498d-ad6d-73fed18f18e8

Lokasyon Computer Science

Tarih 2022

Örnek Metin This paper aims to present WordNet and Wikipedia connection by linking synsets from Turkish WordNet KeNet with Wikipedia and thus, provide a better machine-readable dictionary to create an NLP model with rich data. For this purpose, manual mapping between two resources is realized and 11,478 synsets are linked to Wikipedia. In addition to this, automatic linking approaches are utilized to analyze possible connection suggestions. Baseline Approach and ElasticSearch Based Approach help identify the potential human annotation errors and analyze the effectiveness of these approaches in linking. Adopting both manual and automatic mapping provides us with an encompassing resource of WordNet and Wikipedia connections.