A systematic review of relation extraction task since the emergence of Transformers
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Abstract (arXiv)
This article presents a systematic review of relation extraction (RE) research since the advent of Transformer-based models. Using an automated framework to collect and annotate publications, we analyze 34 surveys, 64 datasets, and 104 models published between 2019 and 2024. The review highlights methodological advances, benchmark resources, and the integration of semantic web technologies. By consolidating results across multiple dimensions, the study identifies current trends, limitations, and open challenges, offering researchers and practitioners a comprehensive reference for understanding the evolution and future directions of RE.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 88 of its 153 references that are in the map. First posted on arXiv 5 Nov 2025.
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