Entity Linking using LLMs for Automated Product Carbon Footprint Estimation

dc.contributor.authorCastle, Steffen
dc.contributor.authorMoreno Schneider, Julian
dc.contributor.editorBasile, Valerio
dc.contributor.editorBosco, Cristina
dc.contributor.editorGrasso, Francesca
dc.contributor.editorIbrahim, Muhammad Okky
dc.contributor.editorSkeppstedt, Maria
dc.contributor.editorStede, Manfred
dc.coverage.spatialTallinn, Estonia
dc.date.accessioned2025-02-17T12:00:46Z
dc.date.available2025-02-17T12:00:46Z
dc.date.issued2025-03
dc.description.abstractGrowing 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.
dc.identifier.isbn978-9908-53-114-4
dc.identifier.urihttps://hdl.handle.net/10062/107182
dc.language.isoen
dc.publisherUniversity of Tartu Library
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.titleEntity Linking using LLMs for Automated Product Carbon Footprint Estimation
dc.typeArticle

Failid

Originaal pakett

Nüüd näidatakse 1 - 1 1
Laen...
Pisipilt
Nimi:
2025_nlp4ecology_1_12.pdf
Suurus:
193.69 KB
Formaat:
Adobe Portable Document Format