Artificial Intelligence

    

Leveraging Large Language Model (LLM)[1] for Natural Language to SQL Query Generation in HR Analytics: A Case Study on IBM Attrition Dataset

Authors: Mayur Sinha, Sangram Kesari Ray, Khirawadhi

This research paper explores the application of the GPT-3.5 Turbo Instruct model for the transformation of natural language queries intostructured SQL queries within the domain of Human Resources (HR) analytics.The study focuses on the IBM Attrition dataset, utilizing the advanced capabilities of the GPT-3.5 Turbo Instruct model to enable efficientand intuitive querying of HR-related data.Employing the model, we conducted experiments to assess its effectiveness in generating SQL queries from diverse natural language inputs,specifically tailored to the nuances of HR analytics questions pertaining to employee attrition within the IBM dataset. By leveraging prompt engineering, with only a few shots, our investigation revealed the model's capacity to accurately understand and interpret complex queries, providing SQL outputs that align with the dataset structure.

Comments: 5 Pages.

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Submission history

[v1] 2024-02-07 04:31:40

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