WordNet and wikipedia connection in Turkish WordNet KeNet

Title WordNet and wikipedia connection in Turkish WordNet KeNet
Author Doğan, M., Oksal, C., Yenice, A. B., Beyhan, F., Yeniterzi, R., Yıldız, Olcay Taner
Publication Date: 2022
Publication Place - European Language Resources Association (ELRA)
Subject Turkish, Wikipedia, WordNet
Type Document
Language English
Digital Yes
Manuscript No
Library: Özyeğin University
Library Asset ID 979-109554692-4
Record ID 92853a5c-6b81-498d-ad6d-73fed18f18e8
Library Location Computer Science
Date 2022
Sample Text 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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WordNet and wikipedia connection in Turkish WordNet KeNet

Author Doğan, M., Oksal, C., Yenice, A. B., Beyhan, F., Yeniterzi, R., Yıldız, Olcay Taner
Publication Date 2022
Publication Place - European Language Resources Association (ELRA)
Subject Turkish, Wikipedia, WordNet
Type Document
Language English
Digital Yes
Manuscript No
Library Özyeğin University
Library Asset ID 979-109554692-4
Record ID 92853a5c-6b81-498d-ad6d-73fed18f18e8
Library Location Computer Science
Date 2022
Sample Text 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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