Papers › A Unified Generative Framework for Various NER Subtasks
A Unified Generative Framework for Various NER Subtasks
Hang Yan, Tao Gui, Junqi Dai, Qipeng Guo, Zheng Zhang, Xipeng Qiu
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.
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Code
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Named Entity Recognition (NER) | CoNLL 2003 (English) | BARTNER | F1 | 93.24 | #28 of 73 | Archive leaderboard | report |
| Named Entity Recognition (NER) | Ontonotes v5 (English) | BARTNER | F1 | 90.38 | #11 of 28 | Archive leaderboard | report |
| Nested Named Entity Recognition | ACE 2004 | BARTNER | F1 | 86.84 | #14 of 24 | Archive leaderboard | report |
| Nested Named Entity Recognition | ACE 2005 | BARTNER | F1 | 84.74 | #14 of 25 | Archive leaderboard | report |
| Nested Named Entity Recognition | GENIA | BARTNER | F1 | 79.23 | #11 of 26 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
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