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A Survey of Deep Learning Methods for Relation Extraction

arXiv 1705.03645 ↗First posted 10 May 2017cs.CLcited by 16

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Abstract (arXiv)

Relation Extraction is an important sub-task of Information Extraction which has the potential of employing deep learning (DL) models with the creation of large datasets using distant supervision. In this review, we compare the contributions and pitfalls of the various DL models that have been used for the task, to help guide the path ahead.

Key facts. Cited by 16 papers in the map (data through 7 Oct 2026). First posted on arXiv 10 May 2017.

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Citing papers per year: 2021: 6; 2022: 2; 2023: 2; 2024: 4; 2025: 2.

16 papers.

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  1. 2022GatorTron: A Large Clinical Language Model to Unlock Patient Information from Unstructured Electronic Health Recordscited by 238
  2. 2021An End-to-end Model for Entity-level Relation Extraction using Multi-instance Learningcited by 31
  3. 2021Deep Neural Approaches to Relation Triplets Extraction: A Comprehensive Surveycited by 12
  4. 2021Deep Neural Network Based Relation Extraction: An Overviewcited by 11
  5. 2021SocAoG: Incremental Graph Parsing for Social Relation Inference in Dialoguescited by 9
  6. 2021Clinical Relation Extraction Using Transformer-based Modelscited by 9
  7. 2024Learning to Extract Structured Entities Using Language Modelscited by 8
  8. 2021Literature review on vulnerability detection using NLP technologycited by 2
  9. 2022gBuilder: A Scalable Knowledge Graph Construction System for Unstructured Corpuscited by 2
  10. 2023Accelerated materials language processing enabled by GPTcited by 0
  11. 2023Relation Extraction from News Articles (RENA): A Tool for Epidemic Surveillancecited by 0
  12. 2024Towards Human-Like Machine Comprehension: Few-Shot Relational Learning in Visually-Rich Documentscited by 0
4 more
  1. 2024Adapting PromptORE for Modern History: Information Extraction from Hispanic Monarchy Documents of the XVIth Centurycited by 0
  2. 2024Maximizing Relation Extraction Potential: A Data-Centric Study to Unveil Challenges and Opportunitiescited by 0
  3. 2025Extracting Structured Requirements from Unstructured Building Technical Specifications for Building Information Modelingcited by 0
  4. 2025Transformer Enhanced Relation Classification: A Comparative Analysis of Contextuality, Data Efficiency and Sequence Complexitycited by 0