Structuring Sustainability Reports for Environmental Standards with LLMs guided by Ontology

Publikation: Beiträge in SammelwerkenAufsätze in KonferenzbändenForschungbegutachtet

Authors

Following the introduction of the European Sustainability Reporting Standard (ESRS), companies will have to adapt to a new policy and provide mandatory sustainability reports. However, implementing such reports entails a challenge, such as the comprehension of a large number of textual information from various sources. This task can be accelerated by employing Large Language Models (LLMs) and ontologies to effectively model the domain knowledge. In this study, we extended an existing ontology to model ESRS Topical Standard for disclosure. The developed ontology would enable automated reasoning over the data and assist in constructing Knowledge Graphs (KGs). Moreover, the proposed ontology extension would also help to identify gaps in companies’ sustainability reports with regard to the ESRS requirements. Additionally, we extracted knowledge from corporate sustainability reports via LLMs guided with a proposed ontology and developed their KG representation.

OriginalspracheEnglisch
TitelClimateNLP 2024 - 1st Workshop on Natural Language Processing Meets Climate Change, Proceedings of the Workshop
HerausgeberDominik Stammbach, Jingwei Ni, Tobias Schimanski, Kalyan Dutia, Alok Singh, Julia Bingler, Christophe Christiaen, Neetu Kushwaha, Veruska Muccione, Saeid A. Vaghefi, Markus Leippold
Anzahl der Seiten10
VerlagAssociation for Computational Linguistics (ACL)
Erscheinungsdatum2024
Seiten168-177
ISBN (elektronisch)979-8-89176-159-9
PublikationsstatusErschienen - 2024
Veranstaltung1st Workshop on Natural Language Processing Meets Climate Change - ClimateNLP 2024 - Bangkok, Thailand
Dauer: 16.08.202416.08.2024
Konferenznummer: 1
https://nlp4climate.github.io/

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©2024 Association for Computational Linguistics.

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