Translating Natural Language Queries to SQL Using the T5 Model
Albert Wong Lien Pham Young Lee Shek Chan Razel Sadaya Youry Khmelevsky Mathias Clement Florence Wing Yau Cheng Joe Mahony Michael Ferri
This paper presents the development process of a natural language to SQL
model using the T5 model as the basis. The models, developed in August 2022 for
an online transaction processing system and a data warehouse, have a 73\% and
84\% exact match accuracy respectively. These models, in conjunction with other
work completed in the research project, were implemented for several companies
and used successfully on a daily basis. The approach used in the model
development could be implemented in a similar fashion for other database
environments and with a more powerful pre-trained language model.