Relation extraction in structured and unstructured data: a comparative investigation on smartphone titles in the e-commerce domain

  • João Gabriel Melo Barbirato UFSCar
  • Livy Real Americanas S. A.
  • Helena de Medeiros Caseli UFSCar


As large amounts of unstructured data are generated on a regular basis, expressing or storing knowledge in a way that is useful remains a challenge. In this context, Relation Extraction (RE) is the task of automatically identifying relationships in unstructured textual data. Thus, we investigated the relation extraction on unstructured e-commerce data from the smartphone domain, using a BERT model fine-tuned for this task. We conducted two experiments to acknowledge how much relational information it is possible to extract from product sheets (structured data) and product titles (unstructured data), and a third experiment to compare both. Analysis shows that extracting relations within a title can retrieve correct relations that are not evident on the related sheet.


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BARBIRATO, João Gabriel Melo; REAL, Livy; CASELI, Helena de Medeiros. Relation extraction in structured and unstructured data: a comparative investigation on smartphone titles in the e-commerce domain. In: SIMPÓSIO BRASILEIRO DE TECNOLOGIA DA INFORMAÇÃO E DA LINGUAGEM HUMANA (STIL), 13. , 2021, Evento Online. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2021 . p. 101-110. DOI: