ChatGPT as a semantic engineering assistant: lessons from ontology design in the agricultural biodiversity domain.
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Modeling species names in biodiversity ontologies is particularly difficult in multilingual contexts, where semantic conflation often occurs. A good example is the common name "pimenta." In Brazilian Portuguese, experts usually refer to Capsicum spp. (chili peppers), while its direct translation “pepper” in English often denotes Piper nigrum (black pepper) (Soares et al. 2025a). In Brazilian markets, however, Piper nigrum is more accurately associated with “pimenta-do-reino" (“pimenta-negra”). This issue was observed on Wikipedia, when translating the Portuguese page for “pimenta” into English, the entry switches from Capsicum spp. to black pepper (Piper nigrum), showing how easily semantic drift can appear in multilingual data modeling. The correct association between common names used in the agricultural market with species would be a way to avoid the misunderstanding of these cultural differences. However, another challenge in vocabulary management emerges, which is how to manage species names in ontologies to keep them updated as the taxonomy itself updates. Some agriculturally controlled vocabularies, such as Agrotermos (Telles et al. 2024) lack automated mechanisms for updating taxonomic classifications. For example, Prochilodus cearensis, Prochilodus scrofa, and Prochilodus margravii are all listed in Agrotermos as preferred terms, i.e., the authorized, standard term selected to represent a concept in a controlled vocabulary, while according to the Global Biodiversity Information Facility (GBIF) Backbone Taxonomy (GBIF Secretariat 2023) these names are synonyms.
Presented at Living Data 2025, Bogotá, Colômbia.
Presented at Living Data 2025, Bogotá, Colômbia.
Palabras clave
Inteligência artificial generativa, Ontologia, Web semântica, Nome científico, Generative IA, Large Language Model, Ontology, Semantic web, Product types, Scientific names, Agricultura, Agriculture, Artificial intelligence