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Event Extraction by Answering (Almost) Natural Questions

arXiv 2004.13625 ↗First posted 28 Apr 2020cs.CLcited by 177

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Abstract (arXiv)

The problem of event extraction requires detecting the event trigger and extracting its corresponding arguments. Existing work in event argument extraction typically relies heavily on entity recognition as a preprocessing/concurrent step, causing the well-known problem of error propagation. To avoid this issue, we introduce a new paradigm for event extraction by formulating it as a question answering (QA) task that extracts the event arguments in an end-to-end manner. Empirical results demonstrate that our framework outperforms prior methods substantially; in addition, it is capable of extracting event arguments for roles not seen at training time (zero-shot learning setting).

Key facts. Cited by 177 papers in the map (data through 7 Oct 2026). First posted on arXiv 28 Apr 2020.

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Citing papers per year: 2021: 32; 2022: 50; 2023: 51; 2024: 27; 2025: 11; 2026: 6.

177 papers.

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  1. 2021Recent Advances in Natural Language Processing via Large Pre-Trained Language Models: A Surveycited by 457
  2. 2023ChatIE: Zero-Shot Information Extraction via Chatting with ChatGPTcited by 250
  3. 2022Unified Structure Generation for Universal Information Extractioncited by 220
  4. 2021Document-Level Event Argument Extraction by Conditional Generationcited by 154
  5. 2023Summary of ChatGPT-Related Research and Perspective Towards the Future of Large Language Modelscited by 152
  6. 2023Evaluating ChatGPT's Information Extraction Capabilities: An Assessment of Performance, Explainability, Calibration, and Faithfulnesscited by 130
  7. 2021Text2Event: Controllable Sequence-to-Structure Generation for End-to-end Event Extractioncited by 129
  8. 2021DEGREE: A Data-Efficient Generation-Based Event Extraction Modelcited by 82
  9. 2023A Survey of GPT-3 Family Large Language Models Including ChatGPT and GPT-4cited by 81
  10. 2023Exploring the Feasibility of ChatGPT for Event Extractioncited by 76
  11. 2021SpartQA: : A Textual Question Answering Benchmark for Spatial Reasoningcited by 75
  12. 2021Label Verbalization and Entailment for Effective Zero- and Few-Shot Relation Extractioncited by 73
38 more
  1. 2022Code4Struct: Code Generation for Few-Shot Event Structure Predictioncited by 70
  2. 2022Prompt for Extraction? PAIE: Prompting Argument Interaction for Event Argument Extractioncited by 54
  3. 2022Generative Knowledge Graph Construction: A Reviewcited by 49
  4. 2021Paradigm Shift in Natural Language Processingcited by 39
  5. 2022PHEE: A Dataset for Pharmacovigilance Event Extraction from Textcited by 36
  6. 2022Dynamic Prefix-Tuning for Generative Template-based Event Extractioncited by 35
  7. 2021ESTER: A Machine Reading Comprehension Dataset for Event Semantic Relation Reasoningcited by 30
  8. 2021Document-level Event Extraction via Heterogeneous Graph-based Interaction Model with a Trackercited by 29
  9. 2022Heroes, Villains, and Victims, and GPT-3: Automated Extraction of Character Roles Without Training Datacited by 27
  10. 2023TextEE: Benchmark, Reevaluation, Reflections, and Future Challenges in Event Extractioncited by 27
  11. 2021Query and Extract: Refining Event Extraction as Type-oriented Binary Decodingcited by 26
  12. 2022Textual Entailment for Event Argument Extraction: Zero- and Few-Shot with Multi-Source Learningcited by 25
  13. 2022GENEVA: Benchmarking Generalizability for Event Argument Extraction with Hundreds of Event Types and Argument Rolescited by 25
  14. 2021OntoED: Low-resource Event Detection with Ontology Embeddingcited by 23
  15. 2023Causal Reasoning of Entities and Events in Procedural Textscited by 23
  16. 2021Asking It All: Generating Contextualized Questions for any Semantic Rolecited by 22
  17. 2022DICE: Data-Efficient Clinical Event Extraction with Generative Modelscited by 20
  18. 2021Corpus-Level Evaluation for Event QA: The IndiaPoliceEvents Corpus Covering the 2002 Gujarat Violencecited by 19
  19. 2021What is Event Knowledge Graph: A Surveycited by 19
  20. 2022Unified Semantic Typing with Meaningful Label Inferencecited by 18
  21. 2022OneEE: A One-Stage Framework for Fast Overlapping and Nested Event Extractioncited by 18
  22. 2022Retrieval-Augmented Generative Question Answering for Event Argument Extractioncited by 18
  23. 2023The Devil is in the Details: On the Pitfalls of Event Extraction Evaluationcited by 18
  24. 2021Corpus-based Open-Domain Event Type Inductioncited by 17
  25. 2022A Two-Stream AMR-enhanced Model for Document-level Event Argument Extractioncited by 16
  26. 2021CasEE: A Joint Learning Framework with Cascade Decoding for Overlapping Event Extractioncited by 15
  27. 2023Event Extraction as Question Generation and Answeringcited by 15
  28. 2021EventNarrative: A large-scale Event-centric Dataset for Knowledge Graph-to-Text Generationcited by 14
  29. 2022Title2Event: Benchmarking Open Event Extraction with a Large-scale Chinese Title Datasetcited by 14
  30. 2022Human-in-the-loop Evaluation for Early Misinformation Detection: A Case Study of COVID-19 Treatmentscited by 14
  31. 2021Dependency Parsing as MRC-based Span-Span Predictioncited by 13
  32. 2021Language Model Priming for Cross-Lingual Event Extractioncited by 13
  33. 2021Efficient Document-level Event Extraction via Pseudo-Trigger-aware Pruned Complete Graphcited by 13
  34. 2021A Survey on Deep Learning Event Extraction: Approaches and Applicationscited by 12
  35. 2023Mask-then-Fill: A Flexible and Effective Data Augmentation Framework for Event Extractioncited by 12
  36. 2024ULTRA: Unleash LLMs' Potential for Event Argument Extraction through Hierarchical Modeling and Pair-wise Self-Refinementcited by 12
  37. 2024Document-level Causal Relation Extraction with Knowledge-guided Binary Question Answeringcited by 12
  38. 2021Capturing Event Argument Interaction via A Bi-Directional Entity-Level Recurrent Decodercited by 11

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