mlsanityData to 7 Oct 2026

Multi-Task Identification of Entities, Relations, and Coreference for Scientific Knowledge Graph Construction

arXiv 1808.09602 ↗First posted 29 Aug 2018cs.CLcited by 321

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Abstract (arXiv)

We introduce a multi-task setup of identifying and classifying entities, relations, and coreference clusters in scientific articles. We create SciERC, a dataset that includes annotations for all three tasks and develop a unified framework called Scientific Information Extractor (SciIE) for with shared span representations. The multi-task setup reduces cascading errors between tasks and leverages cross-sentence relations through coreference links. Experiments show that our multi-task model outperforms previous models in scientific information extraction without using any domain-specific features. We further show that the framework supports construction of a scientific knowledge graph, which we use to analyze information in scientific literature.

Key facts. Cited by 321 papers in the map (data through 7 Oct 2026). First posted on arXiv 29 Aug 2018.

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Citing papers per year: 2021: 52; 2022: 61; 2023: 86; 2024: 64; 2025: 29; 2026: 29.

321 papers.

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  1. 2021Merging Models with Fisher-Weighted Averagingcited by 613
  2. 2023Data Selection for Language Models via Importance Resamplingcited by 322
  3. 2021RadGraph: Extracting Clinical Entities and Relations from Radiology Reportscited by 310
  4. 2023Camels in a Changing Climate: Enhancing LM Adaptation with Tulu 2cited by 227
  5. 2022Unified Structure Generation for Universal Information Extractioncited by 220
  6. 2023Continual Pre-training of Language Modelscited by 194
  7. 2023Large Language Models for Generative Information Extraction: A Surveycited by 183
  8. 2023SciMON: Scientific Inspiration Machines Optimized for Noveltycited by 174
  9. 2023InstructUIE: Multi-task Instruction Tuning for Unified Information Extractioncited by 167
  10. 2023Evaluating ChatGPT's Information Extraction Capabilities: An Assessment of Performance, Explainability, Calibration, and Faithfulnesscited by 130
  11. 2021Lifelong Pretraining: Continually Adapting Language Models to Emerging Corporacited by 114
  12. 2021BERT: A Review of Applications in Natural Language Processing and Understandingcited by 109
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  1. 2023LLMs for Knowledge Graph Construction and Reasoning: Recent Capabilities and Future Opportunitiescited by 97
  2. 2024A Comprehensive Survey of Scientific Large Language Models and Their Applications in Scientific Discoverycited by 96
  3. 2021Time Waits for No One! Analysis and Challenges of Temporal Misalignmentcited by 91
  4. 2021MS2: Multi-Document Summarization of Medical Studiescited by 80
  5. 2022Black-box Prompt Learning for Pre-trained Language Modelscited by 70
  6. 2023UniversalNER: Targeted Distillation from Large Language Models for Open Named Entity Recognitioncited by 70
  7. 2024Extract, Define, Canonicalize: An LLM-based Framework for Knowledge Graph Constructioncited by 70
  8. 2023CodeIE: Large Code Generation Models are Better Few-Shot Information Extractorscited by 67
  9. 2021Can We Automate Scientific Reviewing?cited by 63
  10. 2023GPT-RE: In-context Learning for Relation Extraction using Large Language Modelscited by 62
  11. 2021Multi-Task Learning in Natural Language Processing: An Overviewcited by 61
  12. 2021Packed Levitated Marker for Entity and Relation Extractioncited by 49
  13. 2022Generative Knowledge Graph Construction: A Reviewcited by 49
  14. 2023Text2KGBench: A Benchmark for Ontology-Driven Knowledge Graph Generation from Textcited by 48
  15. 2023Universal Information Extraction as Unified Semantic Matchingcited by 47
  16. 2024Let's Learn Step by Step: Enhancing In-Context Learning Ability with Curriculum Learningcited by 47
  17. 2021A Partition Filter Network for Joint Entity and Relation Extractioncited by 42
  18. 2022A Decade of Knowledge Graphs in Natural Language Processing: A Surveycited by 40
  19. 2023Retrieval-Augmented Code Generation for Universal Information Extractioncited by 40
  20. 2021A Survey on Neural-symbolic Learning Systemscited by 39
  21. 2021UniRE: A Unified Label Space for Entity Relation Extractioncited by 38
  22. 2022Revise and Resubmit: An Intertextual Model of Text-based Collaboration in Peer Reviewcited by 37
  23. 2024SciRIFF: A Resource to Enhance Language Model Instruction-Following over Scientific Literaturecited by 37
  24. 2021Adapt-and-Distill: Developing Small, Fast and Effective Pretrained Language Models for Domainscited by 36
  25. 2021Efficient Domain Adaptation of Language Models via Adaptive Tokenizationcited by 34
  26. 2021NLP From Scratch Without Large-Scale Pretraining: A Simple and Efficient Frameworkcited by 34
  27. 2022Continual Training of Language Models for Few-Shot Learningcited by 33
  28. 2024KnowCoder: Coding Structured Knowledge into LLMs for Universal Information Extractioncited by 33
  29. 2024Get more for less: Principled Data Selection for Warming Up Fine-Tuning in LLMscited by 32
  30. 2021An End-to-end Model for Entity-level Relation Extraction using Multi-instance Learningcited by 31
  31. 2023How to Unleash the Power of Large Language Models for Few-shot Relation Extraction?cited by 30
  32. 2021TDMSci: A Specialized Corpus for Scientific Literature Entity Tagging of Tasks Datasets and Metricscited by 29
  33. 2022Performance Optimization for Semantic Communications: An Attention-based Reinforcement Learning Approachcited by 28
  34. 2023CodeKGC: Code Language Model for Generative Knowledge Graph Constructioncited by 28
  35. 2024TSDS: Data Selection for Task-Specific Model Finetuningcited by 28
  36. 2022Neuro-Symbolic Entropy Regularizationcited by 27
  37. 2021A Trigger-Sense Memory Flow Framework for Joint Entity and Relation Extractioncited by 26
  38. 2021Should We Be Pre-training? An Argument for End-task Aware Training as an Alternativecited by 26

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