Process / pipeline

Relation Extraction — Semantic Relations Between Entities

Relation extraction is a natural-language-processing task that detects and classifies the semantic relations that hold between entities mentioned in text. Building on early kernel-based methods (Zelenko and colleagues, 2003) and later neural matching approaches (Baldini Soares and colleagues, 2019), it turns free-form text into structured facts of the form entity–relation–entity.

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Sources

  1. Zelenko, D., Aone, C. & Richardella, A. (2003). Kernel Methods for Relation Extraction. Journal of Machine Learning Research, 3, 1083-1106. link
  2. Soares, L. B., FitzGerald, N., Ling, J. & Kwiatkowski, T. (2019). Matching the Blanks: Distributional Similarity for Relation Learning. Proceedings of ACL 2019. DOI: 10.18653/v1/P19-1279

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Referenced by

ScholarGateRelation Extraction (Relation Extraction (Semantic Relation Extraction)). Retrieved 2026-06-04 from https://scholargate.app/en/text-mining/relation-extraction