Smirnova, Alisa Cudré-Mauroux, Philippe 2018 Relation extraction is a subtask of information extraction where semantic relationships are extracted from natural language text and then classified. In essence, it allows us to acquire structured knowledge from unstructured text. In this article, we present a survey of relation extraction methods that leverage pre-existing structured or semi- structured data to guide the extraction process. We introduce a taxonomy of existing methods and describe distant supervision approaches in detail. We describe, in addition, the evaluation methodologies and the datasets commonly used for quality assessment. Finally, we give a high-level outlook on the field, highlighting open problems as well as the most promising research directions. application/pdf https://folia.unifr.ch/global/documents/307719 https://folia.unifr.ch/documents/307719/files/cud_reu.pdf eng info:eu-repo/semantics/altIdentifier/doi/10.1145/3241741 info:eu-repo/semantics/openAccess License undefined ACM Comput. Surv.. - 2018, vol. 51, no. 5, p. 106:1–106:35 info:eu-repo/classification/udc/65 Relation extraction using distant supervision: a survey http://purl.org/coar/resource_type/c_6501