Abstract

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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