NER-Luxury: Named entity recognition for the fashion and luxury domain
<|reference_start|>NER-Luxury: Named entity recognition for the fashion and luxury domain: In this study, we address multiple challenges of developing a named-entity recognition model in English for the fashion and luxury industry, namely the entity disambiguation, French technical jargon in multiple sub-sectors, scarcity of the ESG methodology, and a disparate company structures of the sector with small and medium-sized luxury houses to large conglomerate leveraging economy of scale.   In this work, we introduce a taxonomy of 36+ entity types with a luxury-oriented annotation scheme, and create a dataset of more than 40K sentences respecting a clear hierarchical classification. We also present five supervised fine-tuned models NER-Luxury for fashion, beauty, watches, jewelry, fragrances, cosmetics, and overall luxury, focusing equally on the aesthetic side and the quantitative side.   In an additional experiment, we compare in a quantitative empirical assessment of the NER performance of our models against the state-of-the-art open-source large language models that show promising results and highlights the benefits of incorporating a bespoke NER model in existing machine learning pipelines.<|reference_end|>
@article{mousterou2024ner-luxury:,
    title={NER-Luxury: Named entity recognition for the fashion and luxury domain},
    author={Akim Mousterou},
    journal={arXiv preprint arXiv:2409.15804},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.15804},
    primaryClass={cs.CL}
}