mlsanityData to 14 Oct 2026

A Unified Generative Framework for Various NER Subtasks

arXiv 2106.01223 ↗First posted 2 Jun 2021cs.CLcited by 141

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Abstract (arXiv)

Named Entity Recognition (NER) is the task of identifying spans that represent entities in sentences. Whether the entity spans are nested or discontinuous, the NER task can be categorized into the flat NER, nested NER, and discontinuous NER subtasks. These subtasks have been mainly solved by the token-level sequence labelling or span-level classification. However, these solutions can hardly tackle the three kinds of NER subtasks concurrently. To that end, we propose to formulate the NER subtasks as an entity span sequence generation task, which can be solved by a unified sequence-to-sequence (Seq2Seq) framework. Based on our unified framework, we can leverage the pre-trained Seq2Seq model to solve all three kinds of NER subtasks without the special design of the tagging schema or ways to enumerate spans. We exploit three types of entity representations to linearize entities into a sequence. Our proposed framework is easy-to-implement and achieves state-of-the-art (SoTA) or near SoTA performance on eight English NER datasets, including two flat NER datasets, three nested NER datasets, and three discontinuous NER datasets.

Key facts. Cited by 141 papers in the map (data through 14 Oct 2026). Builds on 36 of its 70 references that are in the map. First posted on arXiv 2 Jun 2021.

Builds on

36 of 70 references.

References · 36

  1. 2017Attention Is All You Needcited by 60,361
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  10. 2016Neural Architectures for Named Entity Recognitioncited by 550
  11. 2015Bidirectional LSTM-CRF Models for Sequence Taggingcited by 546
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24 more
  1. 2017Non-Autoregressive Neural Machine Translationcited by 463
  2. 2019MASS: Masked Sequence to Sequence Pre-training for Language Generationcited by 347
  3. 2020LUKE: Deep Contextualized Entity Representations with Entity-aware Self-attentioncited by 326
  4. 2015Named Entity Recognition with Bidirectional LSTM-CNNscited by 201
  5. 2019A Unified MRC Framework for Named Entity Recognitioncited by 199
  6. 2020Named Entity Recognition as Dependency Parsingcited by 151
  7. 2019A General Framework for Information Extraction using Dynamic Span Graphscited by 93
  8. 2018Semi-Supervised Sequence Modeling with Cross-View Trainingcited by 75
  9. 2019TENER: Adapting Transformer Encoder for Named Entity Recognitioncited by 69
  10. 2020FLAT: Chinese NER Using Flat-Lattice Transformercited by 67
  11. 2019Neural Architectures for Nested NER through Linearizationcited by 56
  12. 2021Does syntax matter? A strong baseline for Aspect-based Sentiment Analysis with RoBERTacited by 41
  13. 2019Nested Named Entity Recognition via Second-best Sequence Learning and Decodingcited by 34
  14. 2019Sequence-to-Nuggets: Nested Entity Mention Detection via Anchor-Region Networkscited by 33
  15. 2020An Effective Transition-based Model for Discontinuous NERcited by 33
  16. 2018Neural Segmental Hypergraphs for Overlapping Mention Recognitioncited by 32
  17. 2015Multilingual Language Processing From Bytescited by 26
  18. 2019Merge and Label: A novel neural network architecture for nested NERcited by 17
  19. 2019Combining Spans into Entities: A Neural Two-Stage Approach for Recognizing Discontiguous Entitiescited by 15
  20. 2018Labeling Gaps Between Words: Recognizing Overlapping Mentions with Mention Separatorscited by 14
  21. 2020Bipartite Flat-Graph Network for Nested Named Entity Recognitioncited by 11
  22. 2018Learning to Recognize Discontiguous Entitiescited by 10
  23. 2020Discontinuous Constituent Parsing as Sequence Labelingcited by 9
  24. 2019A Graph-based Model for Joint Chinese Word Segmentation and Dependency Parsingcited by 6

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Citing papers per year: 2021: 11; 2022: 42; 2023: 52; 2024: 26; 2025: 6; 2026: 4.

141 papers.

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  2. 2021Recent Advances in Natural Language Processing via Large Pre-Trained Language Models: A Surveycited by 463
  3. 2022Unified Structure Generation for Universal Information Extractioncited by 221
  4. 2023Large Language Models for Generative Information Extraction: A Surveycited by 185
  5. 2021Unified Named Entity Recognition as Word-Word Relation Classificationcited by 90
  6. 2023When Large Language Models Meet Personalization: Perspectives of Challenges and Opportunitiescited by 90
  7. 2023GLiNER: Generalist Model for Named Entity Recognition using Bidirectional Transformercited by 88
  8. 2022BioBART: Pretraining and Evaluation of A Biomedical Generative Language Modelcited by 83
  9. 2023CodeIE: Large Code Generation Models are Better Few-Shot Information Extractorscited by 68
  10. 2022UniMSE: Towards Unified Multimodal Sentiment Analysis and Emotion Recognitioncited by 61
  11. 2021MAVE: A Product Dataset for Multi-source Attribute Value Extractioncited by 53
  12. 2021Packed Levitated Marker for Entity and Relation Extractioncited by 49
38 more
  1. 2022Generative Knowledge Graph Construction: A Reviewcited by 49
  2. 2021Text-to-Table: A New Way of Information Extractioncited by 47
  3. 2022DeepStruct: Pretraining of Language Models for Structure Predictioncited by 45
  4. 2023LasUIE: Unifying Information Extraction with Latent Adaptive Structure-aware Generative Language Modelcited by 43
  5. 2022Multilingual Generative Language Models for Zero-Shot Cross-Lingual Event Argument Extractioncited by 40
  6. 2021Paradigm Shift in Natural Language Processingcited by 39
  7. 2022InstructionNER: A Multi-Task Instruction-Based Generative Framework for Few-shot NERcited by 31
  8. 2023CodeKGC: Code Language Model for Generative Knowledge Graph Constructioncited by 28
  9. 2021LightNER: A Lightweight Tuning Paradigm for Low-resource NER via Pluggable Promptingcited by 27
  10. 2023DiffuSum: Generation Enhanced Extractive Summarization with Diffusioncited by 25
  11. 2022Optimizing Bi-Encoder for Named Entity Recognition via Contrastive Learningcited by 24
  12. 2023NBIAS: A Natural Language Processing Framework for Bias Identification in Textcited by 23
  13. 2024C-ICL: Contrastive In-context Learning for Information Extractioncited by 23
  14. 2022Decomposed Meta-Learning for Few-Shot Named Entity Recognitioncited by 22
  15. 2023Evaluation of ChatGPT on Biomedical Tasks: A Zero-Shot Comparison with Fine-Tuned Generative Transformerscited by 22
  16. 2021Bottom-Up Constituency Parsing and Nested Named Entity Recognition with Pointer Networkscited by 21
  17. 2022DICE: Data-Efficient Clinical Event Extraction with Generative Modelscited by 20
  18. 2022Parallel Instance Query Network for Named Entity Recognitioncited by 19
  19. 2023AMPERE: AMR-Aware Prefix for Generation-Based Event Argument Extraction Modelcited by 19
  20. 2021Fusing Heterogeneous Factors with Triaffine Mechanism for Nested Named Entity Recognitioncited by 18
  21. 2023Identifying and Extracting Rare Disease Phenotypes with Large Language Modelscited by 18
  22. 2022DeepKE: A Deep Learning Based Knowledge Extraction Toolkit for Knowledge Base Populationcited by 17
  23. 2022MINER: Improving Out-of-Vocabulary Named Entity Recognition from an Information Theoretic Perspectivecited by 17
  24. 2023PromptNER: Prompt Locating and Typing for Named Entity Recognitioncited by 17
  25. 2023UniSA: Unified Generative Framework for Sentiment Analysiscited by 17
  26. 2022Few-shot Named Entity Recognition with Self-describing Networkscited by 16
  27. 2023A Sequence-to-Sequence&Set Model for Text-to-Table Generationcited by 16
  28. 2022Transforming Sequence Tagging Into A Seq2Seq Taskcited by 15
  29. 2022Nested Named Entity Recognition as Latent Lexicalized Constituency Parsingcited by 14
  30. 2024Rethinking Negative Instances for Generative Named Entity Recognitioncited by 13
  31. 2023Mirror: A Universal Framework for Various Information Extraction Taskscited by 12
  32. 2023One Model for All Domains: Collaborative Domain-Prefix Tuning for Cross-Domain NERcited by 11
  33. 2022BIOS: An Algorithmically Generated Biomedical Knowledge Graphcited by 10
  34. 2022PUnifiedNER: A Prompting-based Unified NER System for Diverse Datasetscited by 10
  35. 2023On the Evolution of Knowledge Graphs: A Survey and Perspectivecited by 10
  36. 2022Sequence Generation with Label Augmentation for Relation Extractioncited by 9
  37. 2022TOE: A Grid-Tagging Discontinuous NER Model Enhanced by Embedding Tag/Word Relations and More Fine-Grained Tagscited by 8
  38. 2023A Survey on Arabic Named Entity Recognition: Past, Recent Advances, and Future Trendscited by 8

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