TUR2SQL: A cross-domain Turkish dataset for Text-to-SQL
Yükleniyor...
Tarih
2023-09-15
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
IEEE
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
The field of converting natural language into corresponding SQL queries using deep learning techniques has attracted significant attention in recent years. While existing Text-to-SQL datasets primarily focus on English and other languages such as Chinese, there is a lack of resources for the Turkish language. In this study, we introduce the first publicly available cross-domain Turkish Text-to-SQL dataset, named TUR2SQL. This dataset consists of 10,809 pairs of natural language statements and their corresponding SQL queries. We conducted experiments using SQLNet and ChatGPT on the TUR2SQL dataset. The experimental results show that SQLNet has limited performance and ChatGPT has superior performance on the dataset. We believe that TUR2SQL provides a foundation for further exploration and advancements in Turkish language-based Text-to-SQL research.
Açıklama
We would like to thank all the participants who took part in the survey mentioned in this study, including the students enrolled in the Database Systems course taught by Asst. Prof. Emine Ekin from FMV Isik University during the Spring semester of 2022, as well as the employees of Huawei Turkey R&D Center. Their valuable contributions were crucial in creating natural language templates for our research.
Anahtar Kelimeler
ChatGPT, Dataset, SQLNet, Text-to-SQL, Natural language processing systems, Cross-domain, Natural languages, Performance, SQL query, Turkish language, Turkishs, Deep learning
Kaynak
8th International Conference on Computer Science and Engineering, UBMK 2023
WoS Q Değeri
Scopus Q Değeri
N/A
Cilt
Sayı
Künye
Kanburoğlu, A. B. & Tek, F. B. (2023). TUR2SQL: A cross-domain Turkish dataset for Text-to-SQL. Paper presented at the 8th International Conference on Computer Science and Engineering, UBMK 2023, 206-211. doi:10.1109/UBMK59864.2023.10286686
