Abstract
In this paper we present a first approach to the application of transformer-based language models to the automatic alignment to sustainable development goals (SDGs). This task is quite relevant for the development of new tools that aim at measuring the engagement degree of the organization’s indicators to the SGDs. Our first experiments show that this task is hard, and that even powerful large language models do not achieve a high accuracy as in other NLP tasks.
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Acknowledgement
This research has been partially funded by the Spanish Ministry of Science under grants PID2021-123152OB-C22 and PDC2021-121097-I00 both funded by the MCIN/AEI/10.13039/501100011033 and by the European Union and FEDER/ERDF (European Regional Development Funds). Mario Soriano is granted by the Generalitat Valenciana through the project INVESTIGO (INVEST/2022/308).
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Soriano, M., Berlanga, R., Lanza-Cruz, I. (2023). On the Problem of Automatically Aligning Indicators to SDGs. In: Pesquita, C., et al. The Semantic Web: ESWC 2023 Satellite Events. ESWC 2023. Lecture Notes in Computer Science, vol 13998. Springer, Cham. https://doi.org/10.1007/978-3-031-43458-7_26
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DOI: https://doi.org/10.1007/978-3-031-43458-7_26
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