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home / papers / 2026 / EXCEEDS: Extracting Complex Events via Nugget-based Grid Modeling in Scientific Domain

EXCEEDS: Extracting Complex Events via Nugget-based Grid Modeling in Scientific Domain

Paper · 2026 · Yi-Fan Lu, Xian-Ling Mao, Bo Wang et al.

Summary

Scientific writing has received little attention in event extraction (EE). Few datasets or methods are designed for it, even though research abstracts pack in many triggers and arguments and often have complicated structures: nested events, discontinuous arguments, and arguments that sit far from their trigger. The authors address this in two ways.

First, they build SciEvents, a document-level, multi-event corpus of manually annotated ACL abstracts. Its schema of 10 event types reflects how abstracts are typically organized: background, related work, method and results. Second, they propose EXCEEDS, an end-to-end framework. It encodes pairwise relations between all tokens of a document in a word-word grid, which turns extraction of complex events into a single grid-modeling problem.

On SciEvents, EXCEEDS outperforms recent EE baselines, including generative ones, both overall and on subsets with complex structures. Scores remain low, however, especially for argument classification and for discontinuous or overlapping nuggets. SciEvents is therefore a demanding new benchmark, and both resources are publicly released.

Key points

  • SciEvents contains 2,508 abstracts (439,890 tokens), with 24,381 events and 56,411 arguments.
  • The schema was refined over four rounds of revision, drawing on input from a team of computer science experts: two faculty members at the professor level and three advanced doctoral candidates.
  • SciEvents is denser than existing domain-specific datasets such as ACE2005, Genia, RAMS, CASIE and WikiEvents. Per 100 tokens it has about 5.54 events, 12.82 arguments and 39.49 nugget tokens. It also marks discontinuous (3.08%) and overlapping (33.70%) nuggets.
  • Error analysis shows that most identification errors are missed mentions: 89.2% for trigger identification and 84.6% for argument identification. Classification errors mostly come from confusing semantically similar types or roles, such as Subject vs. Object.
  • The main limitations are coverage of abstracts only and the NLP sub-domain only. Code and data are at github.com/HammerScholar/EXCEEDS.

Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.

 Institutions

🏢Microsoft Research AsiaBeijing · China73 works · 60,539 citations🎓Beijing Institute of TechnologyBeijing · China34 works · 3,652 citations

 Fields, topics and concepts

📚 Shelves 6The field of science this work belongs to (OpenAlex fields).Computer Science · 16,667 worksArtificial Intelligence · 16,194 worksArts and Humanities · 16,039 worksLanguage and Linguistics · 15,891 worksBiochemistry, Genetics and Molecular Biology · 234 worksMolecular Biology · 231 works

Cite

Cite as Yi-Fan Lu, Xian-Ling Mao, Bo Wang, Xiao Liu and Heyan Huang. 2026. EXCEEDS: Extracting Complex Events via Nugget-based Grid Modeling in Scientific Domain. Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers).

The paper itself, not this page. BibTeX from the library's record of the work. DOI 10.18653/v1/2026.acl-long.271

@inproceedings{lu2026exceeds,
  title = {{EXCEEDS: Extracting Complex Events via Nugget-based Grid Modeling in Scientific Domain}},
  author = {Yi-Fan Lu, Xian-Ling Mao, Bo Wang, Xiao Liu and Heyan Huang},
  booktitle = {Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
  year = {2026},
  doi = {10.18653/v1/2026.acl-long.271},
  url = {https://doi.org/10.18653/v1/2026.acl-long.271}
}

References

63 references, 25 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

  1. Jacqueline Aguilar, Charley Beller, Paul McNamee, Benjamin Van Durme, Stephanie Strassel, Zhiyi Song, and Joe Ellis. 2014. A comparison of the events and relations across ACE, ERE, TAC-KBP, and FrameNet annotation standards. In Proceedings of the Second Workshop on EVENTS: Definition, Detection, Cor…
  2. Yunmo Chen, Tongfei Chen, Seth Ebner, Aaron Steven White, and Benjamin Van Durme. 2020. Reading the manual: Event extraction as definition comprehension. In Proceedings of the Fourth Workshop on Structured Prediction for NLP, pages 74–83, Online. Association for Computational Linguistics. find
  3. George Doddington, Alexis Mitchell, Mark Przybocki, Lance Ramshaw, Stephanie Strassel, and Ralph Weischedel. 2004. The automatic content extraction (ACE) program – tasks, data, and evaluation. In Proceedings of the Fourth International Conference on Language Resources and Evaluation (LREC’04), Lisbo…
  4. Xinya Du and Claire Cardie. 2020. Event extraction by answering (almost) natural questions. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 671–683, Online. Association for Computational Linguistics.
  5. Seth Ebner, Patrick Xia, Ryan Culkin, Kyle Rawlins, and Benjamin Van Durme. 2020. Multi-sentence argument linking. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 8057–8077, Online. Association for Computational Linguistics.
  6. Jun Gao, Huan Zhao, Changlong Yu, and Ruifeng Xu. 2023a. Exploring the feasibility of chatgpt for event extraction. arXiv preprint arXiv:2303.03836.
  7. Jun Gao, Huan Zhao, Yice Zhang, Wei Wang, Changlong Yu, and Ruifeng Xu. 2023b. Benchmarking large language models with augmented instructions for fine-grained information extraction. arXiv preprint arXiv:2310.05092. — [arXiv:2310.05092](https://arxiv.org/abs/2310.05092) find
  8. Fayuan Li, Weihua Peng, Yuguang Chen, Quan Wang, Lu Pan, Yajuan Lyu, and Yong Zhu. 2020a. Event extraction as multi-turn question answering. In Findings of the Association for Computational Linguistics: EMNLP 2020, pages 829–838.
  9. I-Hung Hsu, Kuan-Hao Huang, Elizabeth Boschee, Scott Miller, Prem Natarajan, Kai-Wei Chang, and Nanyun Peng. 2022. DEGREE: A data-efficient generation-based event extraction model. In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: H…
  10. Manling Li, Alireza Zareian, Qi Zeng, Spencer Whitehead, Di Lu, Heng Ji, and Shih-Fu Chang. 2020b. Cross-media structured common space for multimedia event extraction. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 2557–2568, Online. Association for… find
  11. I-Hung Hsu, Kuan-Hao Huang, Shuning Zhang, Wenxin Cheng, Prem Natarajan, Kai-Wei Chang, and Nanyun Peng. 2023. TAGPRIME: A unified framework for relational structure extraction. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages… find
  12. Edward J. Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen. 2021. Lora: Low-rank adaptation of large language models. Preprint, arXiv:2106.09685.
  13. Kuan-Hao Huang, I-Hung Hsu, Tanmay Parekh, Zhiyu Xie, Zixuan Zhang, Prem Natarajan, Kai-Wei Chang, Nanyun Peng, and Heng Ji. 2024. TextEE: Benchmark, reevaluation, reflections, and future challenges in event extraction. In Findings of the Association for Computational Linguistics: ACL 2024, pages 12… find
  14. Zhiheng Huang, Wei Xu, and Kai Yu. 2015. Bidirectional lstm-crf models for sequence tagging. Preprint, arXiv:1508.01991.
  15. Jin-Dong Kim, Yue Wang, Toshihisa Takagi, and Akinori Yonezawa. 2011. Overview of Genia event task in BioNLP shared task 2011. In Proceedings of BioNLP Shared Task 2011 Workshop, pages 7–15, Portland, Oregon, USA. Association for Computational Linguistics. find
  16. Jin-Dong Kim, Yue Wang, and Yamamoto Yasunori. 2013. The Genia event extraction shared task, 2013 edition - overview. In Proceedings of the BioNLP Shared Task 2013 Workshop, pages 8–15, Sofia, Bulgaria. Association for Computational Linguistics. find
  17. Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Veselin Stoyanov, and Luke Zettlemoyer. 2020. BART: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension. In Proceedings of the 58th Annual Meeting of the…
  18. Sha Li, Heng Ji, and Jiawei Han. 2021. Document-level event argument extraction by conditional generation. In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 894–908, Online. Association for Computa…
  19. Xinyu Li, Fayuan Li, Lu Pan, Yuguang Chen, Weihua Peng, Quan Wang, Yajuan Lyu, and Yong Zhu. 2020c. Duee: a large-scale dataset for chinese event extraction in real-world scenarios. In Natural Language Processing and Chinese Computing: 9th CCF International Conference, NLPCC 2020, Zhengzhou, China,… find
  20. Zixuan Li, Yutao Zeng, Yuxin Zuo, Weicheng Ren, Wenxuan Liu, Miao Su, Yucan Guo, Yantao Liu, Xiang Li, Zhilei Hu, Long Bai, Wei Li, Yidan Liu, Pan Yang, Xiaolong Jin, Jiafeng Guo, and Xueqi Cheng. 2024. KnowCoder: Coding structured knowledge into LLMs for universal information extraction. In Proceed…
  21. Xin Liang, Dawei Cheng, Fangzhou Yang, Yifeng Luo, Weining Qian, and Aoying Zhou. 2020. F-hmtc: Detecting financial events for investment decisions based on neural hierarchical multi-label text classification. In Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligen… find
  22. Ying Lin, Heng Ji, Fei Huang, and Lingfei Wu. 2020. A joint neural model for information extraction with global features. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 7999–8009, Online. Association for Computational Linguistics.
  23. Chengyuan Liu, Fubang Zhao, Yangyang Kang, Jingyuan Zhang, Xiang Zhou, Changlong Sun, Kun Kuang, and Fei Wu. 2023. RexUIE: A recursive method with explicit schema instructor for universal information extraction. In Findings of the Association for Computational Linguistics: EMNLP 2023, pages 15342–15… find
  24. Ruibo Liu, Jason Wei, Chenyan Jia, and Soroush Vosoughi. 2021. Modulating language models with emotions. In Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, pages 4332–4339, Online. Association for Computational Linguistics. find
  25. Wanlong Liu, Li Zhou, DingYi Zeng, Yichen Xiao, Shaohuan Cheng, Chen Zhang, Grandee Lee, Malu Zhang, and Wenyu Chen. 2024. Beyond single-event extraction: Towards efficient document-level multi-event argument extraction. In Findings of the Association for Computational Linguistics: ACL 2024, pages 9… find
  26. Xiao Liu, Heyan Huang, Ge Shi, and Bo Wang. 2022. Dynamic prefix-tuning for generative template-based event extraction. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 5216–5228, Dublin, Ireland. Association for Computational…
  27. Xiao Liu, Heyan Huang, and Yue Zhang. 2019a. Open domain event extraction using neural latent variable models. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 2860–2871, Florence, Italy. Association for Computational Linguistics. find
  28. Xiao Liu, Zhunchen Luo, and Heyan Huang. 2018. Jointly multiple events extraction via attention-based graph information aggregation. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pages 1247–1256, Brussels, Belgium. Association for Computational Linguistic…
  29. Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019b. Roberta: A robustly optimized bert pretraining approach. Preprint, arXiv:1907.11692.
  30. Jie Lou, Yaojie Lu, Dai Dai, Wei Jia, Hongyu Lin, Xianpei Han, Le Sun, and Hua Wu. 2023. Universal information extraction as unified semantic matching. Proceedings of the AAAI Conference on Artificial Intelligence, 37(11):13318–13326. find
  31. Yaojie Lu, Hongyu Lin, Jin Xu, Xianpei Han, Jialong Tang, Annan Li, Le Sun, Meng Liao, and Shaoyi Chen. 2021. Text2Event: Controllable sequence-to-structure generation for end-to-end event extraction. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the…
  32. Yaojie Lu, Qing Liu, Dai Dai, Xinyan Xiao, Hongyu Lin, Xianpei Han, Le Sun, and Hua Wu. 2022. Unified structure generation for universal information extraction. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 5755–5772, Dublin… find
  33. Mingyu Derek Ma, Alexander Taylor, Wei Wang, and Nanyun Peng. 2023. DICE: Data-efficient clinical event extraction with generative models. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 15898–15917, Toronto, Canada. Associati… find
  34. Yubo Ma, Zehao Wang, Yixin Cao, Mukai Li, Meiqi Chen, Kun Wang, and Jing Shao. 2022. Prompt for extraction? PAIE: Prompting argument interaction for event argument extraction. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 67…
  35. Hieu Man Duc Trong, Duc Trong Le, Amir Pouran Ben Veyseh, Thuat Nguyen, and Thien Huu Nguyen. 2020. Introducing a new dataset for event detection in cybersecurity texts. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 5381–5390, Online. Associ… find
  36. Minh Van Nguyen, Viet Dac Lai, and Thien Huu Nguyen. 2021. Cross-task instance representation interactions and label dependencies for joint information extraction with graph convolutional networks. In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computation… find
  37. Tanmay Parekh, I-Hung Hsu, Kuan-Hao Huang, Kai-Wei Chang, and Nanyun Peng. 2023. GENEVA: Benchmarking generalizability for event argument extraction with hundreds of event types and argument roles. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1:… find
  38. Hao Peng, Xiaozhi Wang, Feng Yao, Kaisheng Zeng, Lei Hou, Juanzi Li, Zhiyuan Liu, and Weixing Shen. 2023. The devil is in the details: On the pitfalls of event extraction evaluation. In Findings of the Association for Computational Linguistics: ACL 2023, pages 9206–9227, Toronto, Canada. Association… find
  39. Amir Pouran Ben Veyseh, Minh Van Nguyen, Franck Dernoncourt, and Thien Nguyen. 2022. MINION: a large-scale and diverse dataset for multilingual event detection. In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Techno… find
  40. Sampo Pyysalo, Tomoko Ohta, Makoto Miwa, Han-Cheol Cho, Jun’ichi Tsujii, and Sophia Ananiadou. 2012. Event extraction across multiple levels of biological organization. Bioinformatics, 28(18):i575– i581. find
  41. Oscar Sainz, Iker García-Ferrero, Rodrigo Agerri, Oier Lopez de Lacalle, German Rigau, and Eneko Agirre. 2024. GoLLIE: Annotation guidelines improve zero-shot information-extraction. In The Twelfth International Conference on Learning Representations.
  42. Taneeya Satyapanich, Francis Ferraro, and Tim Finin. 2020. Casie: Extracting cybersecurity event information from text. Proceedings of the AAAI Conference on Artificial Intelligence, 34(05):8749–8757. find
  43. Shirong Shen, Guilin Qi, Zhen Li, Sheng Bi, and Lusheng Wang. 2020. Hierarchical Chinese legal event extraction via pedal attention mechanism. In Proceedings of the 28th International Conference on Computational Linguistics, pages 100–113, Barcelona, Spain (Online). International Committee on Comput… find
  44. Matthew Sims, Jong Ho Park, and David Bamman. 2019. Literary event detection. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 3623–3634, Florence, Italy. Association for Computational Linguistics. find
  45. Zhiyi Song, Ann Bies, Stephanie Strassel, Tom Riese, Justin Mott, Joe Ellis, Jonathan Wright, Seth Kulick, Neville Ryant, and Xiaoyi Ma. 2015. From light to rich ERE: Annotation of entities, relations, and events. In Proceedings of the The 3rd Workshop on EVENTS: Definition, Detection, Coreference,…
  46. Jianlin Su, Mingren Zhu, Ahmed Murtadha, Shengfeng Pan, Bo Wen, and Yunfeng Liu. 2022. Zlpr: A novel loss for multi-label classification. Preprint, arXiv:2208.02955. — [arXiv:2208.02955](https://arxiv.org/abs/2208.02955) find
  47. Zhaoyue Sun, Jiazheng Li, Gabriele Pergola, Byron Wallace, Bino John, Nigel Greene, Joseph Kim, and Yulan He. 2022. PHEE: A dataset for pharmacovigilance event extraction from text. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, pages 5571–5587, Abu Dhabi,… find
  48. Beth M. Sundheim. 1992. Overview of the fourth Message Understanding Evaluation and Conference. In Fourth Message Understanding Conference (MUC-4): Proceedings of a Conference Held in McLean, Virginia, June 16-18, 1992. find
  49. MeiHan Tong, Bin Xu, Shuai Wang, Meihuan Han, Yixin Cao, Jiangqi Zhu, Siyu Chen, Lei Hou, and Juanzi Li. 2022. DocEE: A large-scale and fine-grained benchmark for document-level event extraction. In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational… find
  50. Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, Dan Bikel, Lukas Blecher, Cristian Canton Ferrer, Moya Chen, Guillem Cucurull, David Esiobu, Jude Fernandes, Jeremy Fu, Wenyin Fu, Brian Fuller,… — Llama 2: Open Foundation and Fine-Tuned Chat Models
  51. Christopher Walker, Stephanie Strassel, Julie Medero, and Kazuaki Maeda. 2006. find
  52. Ace 2005 multilingual training corpus. Techbical report, Linguistic Data Consortium. find
  53. Bo Wang, Heyan Huang, Xiaochi Wei, Ge Shi, Xiao Liu, Chong Feng, Tong Zhou, Shuaiqiang Wang, and Dawei Yin. 2023a. Boosting event extraction with denoised structure-to-text augmentation. In Findings of the Association for Computational Linguistics: ACL 2023, pages 11267–11281, Toronto, Canada. Assoc… find
  54. Xiao Wang, Weikang Zhou, Can Zu, Han Xia, Tianze Chen, Yuansen Zhang, Rui Zheng, Junjie Ye, Qi Zhang, Tao Gui, et al. 2023b. Instructuie: Multi-task instruction tuning for unified information extraction. arXiv preprint arXiv:2304.08085.
  55. Xiaozhi Wang, Ziqi Wang, Xu Han, Wangyi Jiang, Rong Han, Zhiyuan Liu, Juanzi Li, Peng Li, Yankai Lin, and Jie Zhou. 2020. MAVEN: A Massive General Domain Event Detection Dataset. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 1652– 1671, Onli…
  56. Kaiwen Wei, Xian Sun, Zequn Zhang, Jingyuan Zhang, Guo Zhi, and Li Jin. 2021. Trigger is not sufficient: Exploiting frame-aware knowledge for implicit event argument extraction. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Join… find
  57. Xiang Wei, Xingyu Cui, Ning Cheng, Xiaobin Wang, Xin Zhang, Shen Huang, Pengjun Xie, Jinan Xu, Yufeng Chen, Meishan Zhang, et al. 2023. Zero-shot information extraction via chatting with chatgpt. arXiv preprint arXiv:2302.10205.
  58. Hang Yang, Yubo Chen, Kang Liu, Yang Xiao, and Jun Zhao. 2018. DCFEE: A document-level Chinese financial event extraction system based on automatically labeled training data. In Proceedings of ACL 2018, System Demonstrations, pages 50–55, Melbourne, Australia. Association for Computational Linguisti… find
  59. Sen Yang, Dawei Feng, Linbo Qiao, Zhigang Kan, and Dongsheng Li. 2019. Exploring pre-trained language models for event extraction and generation. In Proceedings of the 57th annual meeting of the association for computational linguistics, pages 5284–5294.
  60. Yu Yang, Jinyu Guo, Kai Shuang, and Chenrui Mao. 2024. Scented-EAE: Stage-customized entity type embedding for event argument extraction. In Findings of the Association for Computational Linguistics: ACL 2024, pages 5222–5235, Bangkok, Thailand. Association for Computational Linguistics. find
  61. Feng Yao, Chaojun Xiao, Xiaozhi Wang, Zhiyuan Liu, Lei Hou, Cunchao Tu, Juanzi Li, Yun Liu, Weixing Shen, and Maosong Sun. 2022. LEVEN: A large-scale Chinese legal event detection dataset. In Findings of the Association for Computational Linguistics: ACL 2022, pages 183–201, Dublin, Ireland. Associa… find
  62. Yang Zhou, Yubo Chen, Jun Zhao, Yin Wu, Jiexin Xu, and Jinlong Li. 2021. What the role is vs. what plays the role: Semi-supervised event argument extraction via dual question answering. In Proceedings of the AAAI conference on artificial intelligence, volume 35, pages 14638–14646. find
  63. Tong Zhu, Junfei Ren, Zijian Yu, Mengsong Wu, Guoliang Zhang, Xiaoye Qu, Wenliang Chen, Zhefeng Wang, Baoxing Huai, and Min Zhang. 2023. Mirror: A universal framework for various information extraction tasks. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing,… find

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