Summary
This paper tackles the problem of extracting structured skills from Turkish job postings and labor market data using large language models. It presents the first systematic LLM-based benchmark for Turkish NLP in workforce analytics.
Contribution
- First systematic LLM benchmark for Turkish skill extraction
- Applies LLMs to labor market analytics in a low-resource language context
- Bridges workforce analytics with modern LLM capabilities
References & Links
- arXiv: https://arxiv.org/abs/2601.22885
- Author: Vahid Faraji, Applied AI Specialist
- Related paper: Multi-Agent Position Classification with Tool Orchestration
- Related paper: Tokalator: A Context Engineering Toolkit
Cite this work
@article{faraji2026turkish,
title = {Leveraging LLMs For Turkish Skill Extraction},
author = {Faraji, Vahid},
journal = {arXiv preprint arXiv:2601.22885},
year = {2026}
}