Structuring Sustainability Reports for Environmental Standards with LLMs guided by Ontology

Publikation: Beiträge in SammelwerkenAufsätze in KonferenzbändenForschungbegutachtet

Standard

Structuring Sustainability Reports for Environmental Standards with LLMs guided by Ontology. / Usmanova, Aida; Usbeck, Ricardo.
ClimateNLP 2024 - 1st Workshop on Natural Language Processing Meets Climate Change, Proceedings of the Workshop. Hrsg. / Dominik Stammbach; Jingwei Ni; Tobias Schimanski; Kalyan Dutia; Alok Singh; Julia Bingler; Christophe Christiaen; Neetu Kushwaha; Veruska Muccione; Saeid A. Vaghefi; Markus Leippold. Association for Computational Linguistics (ACL), 2024. S. 168-177 (ClimateNLP 2024 - 1st Workshop on Natural Language Processing Meets Climate Change, Proceedings of the Workshop).

Publikation: Beiträge in SammelwerkenAufsätze in KonferenzbändenForschungbegutachtet

Harvard

Usmanova, A & Usbeck, R 2024, Structuring Sustainability Reports for Environmental Standards with LLMs guided by Ontology. in D Stammbach, J Ni, T Schimanski, K Dutia, A Singh, J Bingler, C Christiaen, N Kushwaha, V Muccione, SA Vaghefi & M Leippold (Hrsg.), ClimateNLP 2024 - 1st Workshop on Natural Language Processing Meets Climate Change, Proceedings of the Workshop. ClimateNLP 2024 - 1st Workshop on Natural Language Processing Meets Climate Change, Proceedings of the Workshop, Association for Computational Linguistics (ACL), S. 168-177, 1st Workshop on Natural Language Processing Meets Climate Change - ClimateNLP 2024, Bangkok, Thailand, 16.08.24. <https://aclanthology.org/2024.climatenlp-1.13/>

APA

Usmanova, A., & Usbeck, R. (2024). Structuring Sustainability Reports for Environmental Standards with LLMs guided by Ontology. In D. Stammbach, J. Ni, T. Schimanski, K. Dutia, A. Singh, J. Bingler, C. Christiaen, N. Kushwaha, V. Muccione, S. A. Vaghefi, & M. Leippold (Hrsg.), ClimateNLP 2024 - 1st Workshop on Natural Language Processing Meets Climate Change, Proceedings of the Workshop (S. 168-177). (ClimateNLP 2024 - 1st Workshop on Natural Language Processing Meets Climate Change, Proceedings of the Workshop). Association for Computational Linguistics (ACL). https://aclanthology.org/2024.climatenlp-1.13/

Vancouver

Usmanova A, Usbeck R. Structuring Sustainability Reports for Environmental Standards with LLMs guided by Ontology. in Stammbach D, Ni J, Schimanski T, Dutia K, Singh A, Bingler J, Christiaen C, Kushwaha N, Muccione V, Vaghefi SA, Leippold M, Hrsg., ClimateNLP 2024 - 1st Workshop on Natural Language Processing Meets Climate Change, Proceedings of the Workshop. Association for Computational Linguistics (ACL). 2024. S. 168-177. (ClimateNLP 2024 - 1st Workshop on Natural Language Processing Meets Climate Change, Proceedings of the Workshop).

Bibtex

@inbook{bb2dc8c6f29c4401be1bae67a6cd4364,
title = "Structuring Sustainability Reports for Environmental Standards with LLMs guided by Ontology",
abstract = "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{\textquoteright} 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.",
keywords = "Informatics",
author = "Aida Usmanova and Ricardo Usbeck",
note = "Publisher Copyright: {\textcopyright}2024 Association for Computational Linguistics.; 1st Workshop on Natural Language Processing Meets Climate Change - ClimateNLP 2024, ClimateNLP 2024 ; Conference date: 16-08-2024 Through 16-08-2024",
year = "2024",
language = "English",
series = "ClimateNLP 2024 - 1st Workshop on Natural Language Processing Meets Climate Change, Proceedings of the Workshop",
publisher = "Association for Computational Linguistics (ACL)",
pages = "168--177",
editor = "Dominik Stammbach and Jingwei Ni and Tobias Schimanski and Kalyan Dutia and Alok Singh and Julia Bingler and Christophe Christiaen and Neetu Kushwaha and Veruska Muccione and Vaghefi, {Saeid A.} and Markus Leippold",
booktitle = "ClimateNLP 2024 - 1st Workshop on Natural Language Processing Meets Climate Change, Proceedings of the Workshop",
address = "United States",
url = "https://nlp4climate.github.io/",

}

RIS

TY - CHAP

T1 - Structuring Sustainability Reports for Environmental Standards with LLMs guided by Ontology

AU - Usmanova, Aida

AU - Usbeck, Ricardo

N1 - Conference code: 1

PY - 2024

Y1 - 2024

N2 - 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.

AB - 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.

KW - Informatics

UR - http://www.scopus.com/inward/record.url?scp=85204423193&partnerID=8YFLogxK

M3 - Article in conference proceedings

AN - SCOPUS:85204423193

T3 - ClimateNLP 2024 - 1st Workshop on Natural Language Processing Meets Climate Change, Proceedings of the Workshop

SP - 168

EP - 177

BT - ClimateNLP 2024 - 1st Workshop on Natural Language Processing Meets Climate Change, Proceedings of the Workshop

A2 - Stammbach, Dominik

A2 - Ni, Jingwei

A2 - Schimanski, Tobias

A2 - Dutia, Kalyan

A2 - Singh, Alok

A2 - Bingler, Julia

A2 - Christiaen, Christophe

A2 - Kushwaha, Neetu

A2 - Muccione, Veruska

A2 - Vaghefi, Saeid A.

A2 - Leippold, Markus

PB - Association for Computational Linguistics (ACL)

T2 - 1st Workshop on Natural Language Processing Meets Climate Change - ClimateNLP 2024

Y2 - 16 August 2024 through 16 August 2024

ER -

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