mlsanityData to 14 Oct 2026

GPT-RE: In-context Learning for Relation Extraction using Large Language Models

arXiv 2305.02105 ↗First posted 3 May 2023cs.CLcited by 62

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Abstract (arXiv)

In spite of the potential for ground-breaking achievements offered by large language models (LLMs) (e.g., GPT-3), they still lag significantly behind fully-supervised baselines (e.g., fine-tuned BERT) in relation extraction (RE). This is due to the two major shortcomings of LLMs in RE: (1) low relevance regarding entity and relation in retrieved demonstrations for in-context learning; and (2) the strong inclination to wrongly classify NULL examples into other pre-defined labels. In this paper, we propose GPT-RE to bridge the gap between LLMs and fully-supervised baselines. GPT-RE successfully addresses the aforementioned issues by (1) incorporating task-specific entity representations in demonstration retrieval; and (2) enriching the demonstrations with gold label-induced reasoning logic. We evaluate GPT-RE on four widely-used RE datasets, and observe that GPT-RE achieves improvements over not only existing GPT-3 baselines, but also fully-supervised baselines. Specifically, GPT-RE achieves SOTA performances on the Semeval and SciERC datasets, and competitive performances on the TACRED and ACE05 datasets.

Key facts. Cited by 62 papers in the map (data through 14 Oct 2026). Builds on 34 of its 44 references that are in the map. First posted on arXiv 3 May 2023.

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34 of 44 references.

References · 34

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2020Language Models are Few-Shot Learnerscited by 32,419
  3. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,599
  4. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,459
  5. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,170
  6. 2022Self-Consistency Improves Chain of Thought Reasoning in Language Modelscited by 5,708
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  8. 2022Large Language Models are Zero-Shot Reasonerscited by 4,374
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22 more
  1. 2015A large annotated corpus for learning natural language inferencecited by 1,847
  2. 2022Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?cited by 1,434
  3. 2019SciBERT: A Pretrained Language Model for Scientific Textcited by 1,414
  4. 2021Calibrate Before Use: Improving Few-Shot Performance of Language Modelscited by 1,392
  5. 2022LaMDA: Language Models for Dialog Applicationscited by 1,220
  6. 2021Scaling Language Models: Methods, Analysis & Insights from Training Gophercited by 1,202
  7. 2021What Makes Good In-Context Examples for GPT-3?cited by 1,195
  8. 2021Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivitycited by 1,135
  9. 2021Learning To Retrieve Prompts for In-Context Learningcited by 648
  10. 2021True Few-Shot Learning with Language Modelscited by 344
  11. 2018Multi-Task Identification of Entities, Relations, and Coreference for Scientific Knowledge Graph Constructioncited by 322
  12. 2019Matching the Blanks: Distributional Similarity for Relation Learningcited by 272
  13. 2018FewRel: A Large-Scale Supervised Few-Shot Relation Classification Dataset with State-of-the-Art Evaluationcited by 254
  14. 2021Constrained Language Models Yield Few-Shot Semantic Parserscited by 163
  15. 2022Thinking about GPT-3 In-Context Learning for Biomedical IE? Think Againcited by 83
  16. 2019SemEval-2010 Task 8: Multi-Way Classification of Semantic Relations Between Pairs of Nominalscited by 63
  17. 2022DeepStruct: Pretraining of Language Models for Structure Predictioncited by 45
  18. 2022Prompting Language Models for Linguistic Structurecited by 39
  19. 2021Coherence boosting: When your pretrained language model is not paying enough attentioncited by 38
  20. 2020Relation Classification as Two-way Span-Predictioncited by 9
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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 18; 2024: 25; 2025: 13; 2026: 6.

62 papers.

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  1. 2023Instruction Tuning for Large Language Models: A Surveycited by 623
  2. 2023Large Language Models for Generative Information Extraction: A Surveycited by 185
  3. 2023Text Classification via Large Language Modelscited by 106
  4. 2024Large Language Models Meet NLP: A Surveycited by 103
  5. 2023LLMs for Knowledge Graph Construction and Reasoning: Recent Capabilities and Future Opportunitiescited by 97
  6. 2023Empirical Study of Zero-Shot NER with ChatGPTcited by 60
  7. 2023Pushing the Limits of ChatGPT on NLP Taskscited by 27
  8. 2023Iterative Zero-Shot LLM Prompting for Knowledge Graph Constructioncited by 25
  9. 2025StructEval: Benchmarking LLMs' Capabilities to Generate Structural Outputscited by 25
  10. 2023Guideline Learning for In-context Information Extractioncited by 24
  11. 2024MMREC: LLM Based Multi-Modal Recommender Systemcited by 22
  12. 2024Biomedical Visual Instruction Tuning with Clinician Preference Alignmentcited by 21
38 more
  1. 2023Position: Key Claims in LLM Research Have a Long Tail of Footnotescited by 20
  2. 2023Chain of Thought with Explicit Evidence Reasoning for Few-shot Relation Extractioncited by 19
  3. 2024ERA-CoT: Improving Chain-of-Thought through Entity Relationship Analysiscited by 18
  4. 2024Automated Construction of Theme-specific Knowledge Graphscited by 16
  5. 2023Cost-Effective In-Context Learning for Entity Resolution: A Design Space Explorationcited by 15
  6. 2024Research Trends for the Interplay between Large Language Models and Knowledge Graphscited by 15
  7. 2024Actionable Cyber Threat Intelligence using Knowledge Graphs and Large Language Modelscited by 14
  8. 2024Meta In-Context Learning Makes Large Language Models Better Zero and Few-Shot Relation Extractorscited by 13
  9. 2023InstructIE: A Bilingual Instruction-based Information Extraction Datasetcited by 9
  10. 2024LLM with Relation Classifier for Document-Level Relation Extractioncited by 8
  11. 2025STRUCTSENSE: A Task-Agnostic Agentic Framework for Structured Information Extraction with Human-In-The-Loop Evaluation and Benchmarkingcited by 8
  12. 2025A Survey on Retrieval And Structuring Augmented Generation with Large Language Modelscited by 8
  13. 2024GenRES: Rethinking Evaluation for Generative Relation Extraction in the Era of Large Language Modelscited by 7
  14. 2024Unlocking Instructive In-Context Learning with Tabular Prompting for Relational Triple Extractioncited by 7
  15. 2023Beyond Isolation: Multi-Agent Synergy for Improving Knowledge Graph Constructioncited by 6
  16. 2024Recall, Retrieve and Reason: Towards Better In-Context Relation Extractioncited by 6
  17. 2023Enhancing In-Context Learning with Answer Feedback for Multi-Span Question Answeringcited by 5
  18. 2024IEPile: Unearthing Large-Scale Schema-Based Information Extraction Corpuscited by 5
  19. 2024Large Language Models can Achieve Social Balancecited by 5
  20. 2024Empirical Analysis of Dialogue Relation Extraction with Large Language Modelscited by 4
  21. 2025Ontology Learning with LLMs: A Benchmark Study on Axiom Identificationcited by 4
  22. 2023GPT-FinRE: In-context Learning for Financial Relation Extraction using Large Language Modelscited by 3
  23. 2023MT4CrossOIE: Multi-stage Tuning for Cross-lingual Open Information Extractioncited by 3
  24. 2023Document-Level In-Context Few-Shot Relation Extraction via Pre-Trained Language Modelscited by 2
  25. 2025Reasoning Pattern Matters: Learning to Reason without Human Rationalescited by 2
  26. 2023Mastering the Task of Open Information Extraction with Large Language Models and Consistent Reasoning Environmentcited by 1
  27. 2024DiMB-RE: Mining the Scientific Literature for Diet-Microbiome Associationscited by 1
  28. 2024Mathematical Derivation Graphs: A Relation Extraction Task in STEM Manuscriptscited by 1
  29. 2024Efficient Alignment of Large Language Models via Data Samplingcited by 1
  30. 2025Crowdsourcing-Based Knowledge Graph Construction for Drug Side Effects Using Large Language Models with an Application on Semaglutidecited by 1
  31. 2024A Two Dimensional Feature Engineering Method for Relation Extractioncited by 0
  32. 2024Enhancing Software-Related Information Extraction via Single-Choice Question Answering with Large Language Modelscited by 0
  33. 2024CRE-LLM: A Domain-Specific Chinese Relation Extraction Framework with Fine-tuned Large Language Modelcited by 0
  34. 2024End-to-End Trainable Retrieval-Augmented Generation for Relation Extractioncited by 0
  35. 2024Empowering Few-Shot Relation Extraction with The Integration of Traditional RE Methods and Large Language Modelscited by 0
  36. 2024Maximizing Relation Extraction Potential: A Data-Centric Study to Unveil Challenges and Opportunitiescited by 0
  37. 2024Extract Information from Hybrid Long Documents Leveraging LLMs: A Framework and Datasetcited by 0
  38. 2025Relation Extraction with Instance-Adapted Predicate Descriptionscited by 0

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