mlsanityData to 7 Oct 2026

InstructIE: A Bilingual Instruction-based Information Extraction Dataset

arXiv 2305.11527 ↗First posted 19 May 2023cs.CL cs.AI cs.IRcited by 9

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Abstract (arXiv)

Large language models can perform well on general natural language tasks, but their effectiveness is still suboptimal for information extraction (IE). Recent works indicate that the main reason lies in the lack of extensive data on IE instructions. Note that the existing datasets on IE instructions not only have limited coverage but also involve high construction costs. To address this issue, we introduce InstructIE, a bilingual instruction-based IE dataset, which covers 12 diverse domains. We propose KG2Instruction, a framework specifically for the automatic generation of such datasets. Additionally, we manually annotate the test set. Experimental results demonstrate that large language models trained with InstructIE can not only obtain better IE capabilities but also enhance zero-shot performance compared with baselines.

Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). Builds on 39 of its 80 references that are in the map. First posted on arXiv 19 May 2023.

Builds on

39 of 80 references.

References · 39

  1. 2020Language Models are Few-Shot Learnerscited by 32,199
  2. 2023GPT-4 Technical Reportcited by 18,132
  3. 2022Training language models to follow instructions with human feedbackcited by 15,712
  4. 2023LLaMA: Open and Efficient Foundation Language Modelscited by 13,958
  5. 2022PaLM: Scaling Language Modeling with Pathwayscited by 5,304
  6. 2021Finetuned Language Models Are Zero-Shot Learnerscited by 3,747
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27 more
  1. 2023ChatIE: Zero-Shot Information Extraction via Chatting with ChatGPTcited by 250
  2. 2022Unified Structure Generation for Universal Information Extractioncited by 220
  3. 2019A Unified MRC Framework for Named Entity Recognitioncited by 199
  4. 2021Structured Prediction as Translation between Augmented Natural Languagescited by 183
  5. 2020Event Extraction by Answering (Almost) Natural Questionscited by 177
  6. 2023InstructUIE: Multi-task Instruction Tuning for Unified Information Extractioncited by 167
  7. 2023GPT-NER: Named Entity Recognition via Large Language Modelscited by 158
  8. 2022Prompting PaLM for Translation: Assessing Strategies and Performancecited by 144
  9. 2023Evaluating ChatGPT's Information Extraction Capabilities: An Assessment of Performance, Explainability, Calibration, and Faithfulnesscited by 130
  10. 2023Large Language Model Is Not a Good Few-shot Information Extractor, but a Good Reranker for Hard Samples!cited by 119
  11. 2017Joint Extraction of Entities and Relations Based on a Novel Tagging Schemecited by 102
  12. 2023Revisiting Relation Extraction in the era of Large Language Modelscited by 100
  13. 2021Label Verbalization and Entailment for Effective Zero- and Few-Shot Relation Extractioncited by 73
  14. 2023CodeIE: Large Code Generation Models are Better Few-Shot Information Extractorscited by 67
  15. 2023GPT-RE: In-context Learning for Relation Extraction using Large Language Modelscited by 62
  16. 2022Generative Knowledge Graph Construction: A Reviewcited by 49
  17. 2019CopyMTL: Copy Mechanism for Joint Extraction of Entities and Relations with Multi-Task Learningcited by 47
  18. 2023Universal Information Extraction as Unified Semantic Matchingcited by 47
  19. 2021ZS-BERT: Towards Zero-Shot Relation Extraction with Attribute Representation Learningcited by 46
  20. 2022PHEE: A Dataset for Pharmacovigilance Event Extraction from Textcited by 36
  21. 2018Improving Distantly Supervised Relation Extraction using Word and Entity Based Attentioncited by 35
  22. 2022Dynamic Prefix-Tuning for Generative Template-based Event Extractioncited by 35
  23. 2021The Stem Cell Hypothesis: Dilemma behind Multi-Task Learning with Transformer Encoderscited by 31
  24. 2020Biomedical Named Entity Recognition at Scalecited by 30
  25. 2019IPRE: a Dataset for Inter-Personal Relationship Extractioncited by 8
  26. 2023Easy-to-Hard Learning for Information Extractioncited by 5
  27. 2023Schema-adaptable Knowledge Graph Constructioncited by 4

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 1; 2024: 2; 2025: 4; 2026: 2.

9 papers.

  1. 2024InstructGraph: Boosting Large Language Models via Graph-centric Instruction Tuning and Preference Alignmentcited by 56
  2. 2025Instruction-Tuning LLMs for Event Extraction with Annotation Guidelinescited by 18
  3. 2023Large Knowledge Model: Perspectives and Challengescited by 12
  4. 2024IEPile: Unearthing Large-Scale Schema-Based Information Extraction Corpuscited by 5
  5. 2025Event Extraction in Large Language Modelcited by 5
  6. 2025GuideX: Guided Synthetic Data Generation for Zero-Shot Information Extractioncited by 3
  7. 2026Tracing the Data Trail: A Survey of Data Provenance, Transparency and Traceability in LLMscited by 3
  8. 2025Structuring the Unstructured: A Systematic Review of Text-to-Structure Generation for Agentic AI with a Universal Evaluation Frameworkcited by 2
  9. 2026SCOPE and SCION: A Benchmark and an Auditable Reference Pipeline for Schema Induction and Fusion from Textcited by 0