Structuring Sustainability Reports for Environmental Standards with LLMs guided by Ontology
Publikation: Beiträge in Sammelwerken › Aufsätze in Konferenzbänden › Forschung › begutachtet
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.
Originalsprache | Englisch |
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Titel | ClimateNLP 2024 - 1st Workshop on Natural Language Processing Meets Climate Change, Proceedings of the Workshop |
Herausgeber | Dominik Stammbach, Jingwei Ni, Tobias Schimanski, Kalyan Dutia, Alok Singh, Julia Bingler, Christophe Christiaen, Neetu Kushwaha, Veruska Muccione, Saeid A. Vaghefi, Markus Leippold |
Anzahl der Seiten | 10 |
Verlag | Association for Computational Linguistics (ACL) |
Erscheinungsdatum | 2024 |
Seiten | 168-177 |
ISBN (elektronisch) | 979-8-89176-159-9 |
Publikationsstatus | Erschienen - 2024 |
Veranstaltung | 1st Workshop on Natural Language Processing Meets Climate Change - ClimateNLP 2024 - Bangkok, Thailand Dauer: 16.08.2024 → 16.08.2024 Konferenznummer: 1 https://nlp4climate.github.io/ |
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