# Sequence-to-Nuggets: Nested Entity Mention Detection via Anchor-Region Networks

arXiv: https://arxiv.org/abs/1906.03783 · HTML: https://mlsanity.com/paper/1906.03783/

## Key facts

- Cited by 33 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 10 Jun 2019.

## Built on by (most cited first, 30 of 33)

- [Unified Structure Generation for Universal Information Extraction](https://mlsanity.com/paper/2203.12277/) (2022)
- [Template-Based Named Entity Recognition Using BART](https://mlsanity.com/paper/2106.01760/) (2021)
- [A Unified Generative Framework for Various NER Subtasks](https://mlsanity.com/paper/2106.01223/) (2021)
- [BioBART: Pretraining and Evaluation of A Biomedical Generative Language Model](https://mlsanity.com/paper/2204.03905/) (2022)
- [Locate and Label: A Two-stage Identifier for Nested Named Entity Recognition](https://mlsanity.com/paper/2105.06804/) (2021)
- [A Sequence-to-Set Network for Nested Named Entity Recognition](https://mlsanity.com/paper/2105.08901/) (2021)
- [A Span-Based Model for Joint Overlapped and Discontinuous Named Entity Recognition](https://mlsanity.com/paper/2106.14373/) (2021)
- [LightNER: A Lightweight Tuning Paradigm for Low-resource NER via Pluggable Prompting](https://mlsanity.com/paper/2109.00720/) (2021)
- [De-biasing Distantly Supervised Named Entity Recognition via Causal Intervention](https://mlsanity.com/paper/2106.09233/) (2021)
- [Fine-grained Entity Typing via Label Reasoning](https://mlsanity.com/paper/2109.05744/) (2021)
- [DaN+: Danish Nested Named Entities and Lexical Normalization](https://mlsanity.com/paper/2105.11301/) (2021)
- [Parallel Instance Query Network for Named Entity Recognition](https://mlsanity.com/paper/2203.10545/) (2022)
- [Fusing Heterogeneous Factors with Triaffine Mechanism for Nested Named Entity Recognition](https://mlsanity.com/paper/2110.07480/) (2021)
- [Few-shot Named Entity Recognition with Self-describing Networks](https://mlsanity.com/paper/2203.12252/) (2022)
- [Nested Named Entity Recognition as Latent Lexicalized Constituency Parsing](https://mlsanity.com/paper/2203.04665/) (2022)
- [Honey or Poison? Solving the Trigger Curse in Few-shot Event Detection via Causal Intervention](https://mlsanity.com/paper/2109.05747/) (2021)
- [Semantic Parsing in Task-Oriented Dialog with Recursive Insertion-based Encoder](https://mlsanity.com/paper/2109.04500/) (2021)
- [ToNER: Type-oriented Named Entity Recognition with Generative Language Model](https://mlsanity.com/paper/2404.09145/) (2024)
- [Denoising Distantly Supervised Named Entity Recognition via a Hypergeometric Probabilistic Model](https://mlsanity.com/paper/2106.09234/) (2021)
- [Propose-and-Refine: A Two-Stage Set Prediction Network for Nested Named Entity Recognition](https://mlsanity.com/paper/2204.12732/) (2022)
- [MR-UIE: Multi-Perspective Reasoning with Reinforcement Learning for Universal Information Extraction](https://mlsanity.com/paper/2509.09082/) (2025)
- [DiffusionNER: Boundary Diffusion for Named Entity Recognition](https://mlsanity.com/paper/2305.13298/) (2023)
- [Universal Information Extraction with Meta-Pretrained Self-Retrieval](https://mlsanity.com/paper/2306.10444/) (2023)
- [P-ICL: Point In-Context Learning for Named Entity Recognition with Large Language Models](https://mlsanity.com/paper/2405.04960/) (2024)
- [Deep Span Representations for Named Entity Recognition](https://mlsanity.com/paper/2210.04182/) (2022)
- [Enhanced Language Representation with Label Knowledge for Span Extraction](https://mlsanity.com/paper/2111.00884/) (2021)
- [Named Entity Recognition in the Style of Object Detection](https://mlsanity.com/paper/2101.11122/) (2021)
- [BoningKnife: Joint Entity Mention Detection and Typing for Nested NER via prior Boundary Knowledge](https://mlsanity.com/paper/2107.09429/) (2021)
- [Effect of depth order on iterative nested named entity recognition models](https://mlsanity.com/paper/2104.01037/) (2021)
- [Nested and Balanced Entity Recognition using Multi-Task Learning](https://mlsanity.com/paper/2106.06216/) (2021)

## Abstract (arXiv)

Sequential labeling-based NER approaches restrict each word belonging to at most one entity mention, which will face a serious problem when recognizing nested entity mentions. In this paper, we propose to resolve this problem by modeling and leveraging the head-driven phrase structures of entity mentions, i.e., although a mention can nest other mentions, they will not share the same head word. Specifically, we propose Anchor-Region Networks (ARNs), a sequence-to-nuggets architecture for nested mention detection. ARNs first identify anchor words (i.e., possible head words) of all mentions, and then recognize the mention boundaries for each anchor word by exploiting regular phrase structures. Furthermore, we also design Bag Loss, an objective function which can train ARNs in an end-to-end manner without using any anchor word annotation. Experiments show that ARNs achieve the state-of-the-art performance on three standard nested entity mention detection benchmarks.