Entity Linking using LLMs for Automated Product Carbon Footprint Estimation

Steffen Castle, Julian Moreno Schneider, Leonhard Hennig, Georg Rehm
2/11/2025
cs.CL

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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.

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Cite this paper

@article{castle2025entity,
  title  = {Entity Linking using LLMs for Automated Product Carbon Footprint Estimation},
  author = {Steffen Castle and Julian Moreno Schneider and Leonhard Hennig and Georg Rehm},
  year   = {2025},
  eprint = {2502.07418},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2502.07418v1}
}

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