mlsanityData to 14 Oct 2026

A Survey on Open Information Extraction from Rule-based Model to Large Language Model

arXiv 2208.08690 ↗First posted 18 Aug 2022cs.CLcited by 8

Not on the map. Why?

Abstract (arXiv)

Open Information Extraction (OpenIE) represents a crucial NLP task aimed at deriving structured information from unstructured text, unrestricted by relation type or domain. This survey paper provides an overview of OpenIE technologies spanning from 2007 to 2024, emphasizing a chronological perspective absent in prior surveys. It examines the evolution of task settings in OpenIE to align with the advances in recent technologies. The paper categorizes OpenIE approaches into rule-based, neural, and pre-trained large language models, discussing each within a chronological framework. Additionally, it highlights prevalent datasets and evaluation metrics currently in use. Building on this extensive review, the paper outlines potential future directions in terms of datasets, information sources, output formats, methodologies, and evaluation metrics.

Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). Builds on 30 of its 139 references that are in the map. First posted on arXiv 18 Aug 2022.

Builds on

30 of 139 references.

References · 30

  1. 2017Attention Is All You Needcited by 60,361
  2. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  3. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,599
  4. 2021Evaluating Large Language Models Trained on Codecited by 8,320
  5. 2019How Can We Know What Language Models Know?cited by 959
  6. 2018FewRel: A Large-Scale Supervised Few-Shot Relation Classification Dataset with State-of-the-Art Evaluationcited by 254
  7. 2022Unified Structure Generation for Universal Information Extractioncited by 221
  8. 2020How Context Affects Language Models' Factual Predictionscited by 181
  9. 2018Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networkscited by 101
  10. 2020More Data, More Relations, More Context and More Openness: A Review and Outlook for Relation Extractioncited by 52
  11. 2018A Survey on Open Information Extractioncited by 51
  12. 2018Neural Open Information Extractioncited by 50
18 more
  1. 2018Large-Scale QA-SRL Parsingcited by 45
  2. 2020SelfORE: Self-supervised Relational Feature Learning for Open Relation Extractioncited by 43
  3. 2020IMoJIE: Iterative Memory-Based Joint Open Information Extractioncited by 34
  4. 2019Span Model for Open Information Extraction on Accurate Corpuscited by 33
  5. 2019CESI: Canonicalizing Open Knowledge Bases using Embeddings and Side Informationcited by 28
  6. 2020Multi2OIE: Multilingual Open Information Extraction Based on Multi-Head Attention with BERTcited by 26
  7. 2021Zero-Shot Information Extraction as a Unified Text-to-Triple Translationcited by 22
  8. 2017Crowdsourcing Question-Answer Meaning Representationscited by 21
  9. 2018WiRe57 : A Fine-Grained Benchmark for Open Information Extractioncited by 16
  10. 2019Logician: A Unified End-to-End Neural Approach for Open-Domain Information Extractioncited by 15
  11. 2021LSOIE: A Large-Scale Dataset for Supervised Open Information Extractioncited by 15
  12. 2021A Relation-Oriented Clustering Method for Open Relation Extractioncited by 15
  13. 2018Unsupervised Open Relation Extractioncited by 14
  14. 2021Element Intervention for Open Relation Extractioncited by 11
  15. 2022DetIE: Multilingual Open Information Extraction Inspired by Object Detectioncited by 11
  16. 2017Analysing Errors of Open Information Extraction Systemscited by 7
  17. 2019Hybrid Neural Tagging Model for Open Relation Extractioncited by 5
  18. 2021Explore BiLSTM-CRF-Based Models for Open Relation Extractioncited by 2

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 4; 2026: 4.

8 papers.

  1. 2025GFM-RAG: Graph Foundation Model for Retrieval Augmented Generationcited by 40
  2. 2025LLM-empowered knowledge graph construction: A surveycited by 21
  3. 2025Fewer Hallucinations, More Verification: A Three-Stage LLM-Based Framework for ASR Error Correctioncited by 7
  4. 2026Knowledge Capsules: Structured Nonparametric Memory Units for LLMscited by 1
  5. 2025Data Overdose? Time for a Quadruple Shot: Knowledge Graph Construction using Enhanced Triple Extractioncited by 0
  6. 2026Hybrid-IR: Dual-Path Hybrid Retrieval with Iterative Reasoning for Complex Medical Question Answeringcited by 0
  7. 2026Enoki: Efficient Multi-Level Hallucination Detectioncited by 0
  8. 2026AAS-RAIL: Improving Information Extraction for Asset Administration Shells through Retrieval-Augmented In-Context Learningcited by 0