English

Entity Linking using LLMs for Automated Product Carbon Footprint Estimation

Computation and Language 2025-02-12 v1

Abstract

Growing concerns about climate change and sustainability are driving manufacturers to take significant steps toward reducing their carbon footprints. For these manufacturers, a first step towards this goal is to identify the environmental impact of the individual components of their products. We propose a system leveraging large language models (LLMs) to automatically map components from manufacturer Bills of Materials (BOMs) to Life Cycle Assessment (LCA) database entries by using LLMs to expand on available component information. Our approach reduces the need for manual data processing, paving the way for more accessible sustainability practices.

Keywords

Cite

@article{arxiv.2502.07418,
  title  = {Entity Linking using LLMs for Automated Product Carbon Footprint Estimation},
  author = {Steffen Castle and Julian Moreno Schneider and Leonhard Hennig and Georg Rehm},
  journal= {arXiv preprint arXiv:2502.07418},
  year   = {2025}
}
R2 v1 2026-06-28T21:40:01.629Z