@inproceedings{dogan-etal-2022-wordnet,
title = "{W}ord{N}et and {W}ikipedia Connection in {T}urkish {W}ord{N}et {K}e{N}et",
author = {Do{\u{g}}an, Merve and
Oksal, Ceren and
Yenice, Arife Bet{\"u}l and
Beyhan, Fatih and
Yeniterzi, Reyyan and
Y{\i}ld{\i}z, Olcay Taner},
editor = "Kernerman, Ilan and
Krek, Simon",
booktitle = "Proceedings of Globalex Workshop on Linked Lexicography within the 13th Language Resources and Evaluation Conference",
month = jun,
year = "2022",
address = "Marseille, France",
publisher = "European Language Resources Association",
url = "https://aclanthology.org/2022.gwll-1.12",
pages = "85--89",
abstract = "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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<abstract>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.</abstract>
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%0 Conference Proceedings
%T WordNet and Wikipedia Connection in Turkish WordNet KeNet
%A Doğan, Merve
%A Oksal, Ceren
%A Yenice, Arife Betül
%A Beyhan, Fatih
%A Yeniterzi, Reyyan
%A Yıldız, Olcay Taner
%Y Kernerman, Ilan
%Y Krek, Simon
%S Proceedings of Globalex Workshop on Linked Lexicography within the 13th Language Resources and Evaluation Conference
%D 2022
%8 June
%I European Language Resources Association
%C Marseille, France
%F dogan-etal-2022-wordnet
%X 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.
%U https://aclanthology.org/2022.gwll-1.12
%P 85-89
Markdown (Informal)
[WordNet and Wikipedia Connection in Turkish WordNet KeNet](https://aclanthology.org/2022.gwll-1.12) (Doğan et al., gwll 2022)
ACL
- Merve Doğan, Ceren Oksal, Arife Betül Yenice, Fatih Beyhan, Reyyan Yeniterzi, and Olcay Taner Yıldız. 2022. WordNet and Wikipedia Connection in Turkish WordNet KeNet. In Proceedings of Globalex Workshop on Linked Lexicography within the 13th Language Resources and Evaluation Conference, pages 85–89, Marseille, France. European Language Resources Association.