# Bottom-Up Constituency Parsing and Nested Named Entity Recognition with Pointer Networks

arXiv: https://arxiv.org/abs/2110.05419 · HTML: https://mlsanity.com/paper/2110.05419/

## Key facts

- Cited by 21 papers in the map (data through 14 Oct 2026).
- Builds on 50 of its 71 references that are in the map.
- First posted on arXiv 11 Oct 2021.

## Builds on (most cited first, 30 of 50)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Adam: A Method for Stochastic Optimization](https://mlsanity.com/paper/1412.6980/) (2014)
- [BioBERT: a pre-trained biomedical language representation model for biomedical text mining](https://mlsanity.com/paper/1901.08746/) (2019)
- [Pointer Networks](https://mlsanity.com/paper/1506.03134/) (2015)
- [Deep Biaffine Attention for Neural Dependency Parsing](https://mlsanity.com/paper/1611.01734/) (2016)
- [Constituency Parsing with a Self-Attentive Encoder](https://mlsanity.com/paper/1805.01052/) (2018)
- [Named Entity Recognition as Dependency Parsing](https://mlsanity.com/paper/2005.07150/) (2020)
- [A Unified Generative Framework for Various NER Subtasks](https://mlsanity.com/paper/2106.01223/) (2021)
- [Multilingual Constituency Parsing with Self-Attention and Pre-Training](https://mlsanity.com/paper/1812.11760/) (2018)
- [Recurrent Neural Network Grammars](https://mlsanity.com/paper/1602.07776/) (2016)
- [Grammar as a Foreign Language](https://mlsanity.com/paper/1412.7449/) (2014)
- [Locate and Label: A Two-stage Identifier for Nested Named Entity Recognition](https://mlsanity.com/paper/2105.06804/) (2021)
- [A Minimal Span-Based Neural Constituency Parser](https://mlsanity.com/paper/1705.03919/) (2017)
- [Fast and Accurate Neural CRF Constituency Parsing](https://mlsanity.com/paper/2008.03736/) (2020)
- [Head-Driven Phrase Structure Grammar Parsing on Penn Treebank](https://mlsanity.com/paper/1907.02684/) (2019)
- [A Sequence-to-Set Network for Nested Named Entity Recognition](https://mlsanity.com/paper/2105.08901/) (2021)
- [Stack-Pointer Networks for Dependency Parsing](https://mlsanity.com/paper/1805.01087/) (2018)
- [Nested Named Entity Recognition via Second-best Sequence Learning and Decoding](https://mlsanity.com/paper/1909.02250/) (2019)
- [A Span-Based Model for Joint Overlapped and Discontinuous Named Entity Recognition](https://mlsanity.com/paper/2106.14373/) (2021)
- [Straight to the Tree: Constituency Parsing with Neural Syntactic Distance](https://mlsanity.com/paper/1806.04168/) (2018)
- [Neural Segmental Hypergraphs for Overlapping Mention Recognition](https://mlsanity.com/paper/1810.01817/) (2018)
- [Constituent Parsing as Sequence Labeling](https://mlsanity.com/paper/1810.08994/) (2018)
- [AMR Parsing with Action-Pointer Transformer](https://mlsanity.com/paper/2104.14674/) (2021)
- [In-Order Transition-based Constituent Parsing](https://mlsanity.com/paper/1707.05000/) (2017)
- [Strongly Incremental Constituency Parsing with Graph Neural Networks](https://mlsanity.com/paper/2010.14568/) (2020)
- [Nested Named Entity Recognition with Partially-Observed TreeCRFs](https://mlsanity.com/paper/2012.08478/) (2020)
- [Left-to-Right Dependency Parsing with Pointer Networks](https://mlsanity.com/paper/1903.08445/) (2019)
- [Span-Based Constituency Parsing with a Structure-Label System and Provably Optimal Dynamic Oracles](https://mlsanity.com/paper/1612.06475/) (2016)
- [Tetra-Tagging: Word-Synchronous Parsing with Linear-Time Inference](https://mlsanity.com/paper/1904.09745/) (2019)
- [Merge and Label: A novel neural network architecture for nested NER](https://mlsanity.com/paper/1907.00464/) (2019)

## Built on by (most cited first, 21 of 21)

- [Unifying Large Language Models and Knowledge Graphs: A Roadmap](https://mlsanity.com/paper/2306.08302/) (2023)
- [Parallel Instance Query Network for Named Entity Recognition](https://mlsanity.com/paper/2203.10545/) (2022)
- [PromptNER: Prompt Locating and Typing for Named Entity Recognition](https://mlsanity.com/paper/2305.17104/) (2023)
- [Nested Named Entity Recognition as Latent Lexicalized Constituency Parsing](https://mlsanity.com/paper/2203.04665/) (2022)
- [BenchCLAMP: A Benchmark for Evaluating Language Models on Syntactic and Semantic Parsing](https://mlsanity.com/paper/2206.10668/) (2022)
- [Linguistic Blind Spots of Large Language Models](https://mlsanity.com/paper/2503.19260/) (2025)
- [A Survey on Semantic Processing Techniques](https://mlsanity.com/paper/2310.18345/) (2023)
- [MedDec: A Dataset for Extracting Medical Decisions from Discharge Summaries](https://mlsanity.com/paper/2408.12980/) (2024)
- [Approximating CKY with Transformers](https://mlsanity.com/paper/2305.02386/) (2023)
- [Constituency Parsing using LLMs](https://mlsanity.com/paper/2310.19462/) (2023)
- [To be Continuous, or to be Discrete, Those are Bits of Questions](https://mlsanity.com/paper/2406.07812/) (2024)
- [Semantic Operator Prediction and Applications](https://mlsanity.com/paper/2301.00399/) (2023)
- [Unleashing the True Potential of Sequence-to-Sequence Models for Sequence Tagging and Structure Parsing](https://mlsanity.com/paper/2302.02275/) (2023)
- [DepNeCTI: Dependency-based Nested Compound Type Identification for Sanskrit](https://mlsanity.com/paper/2310.09501/) (2023)
- [AMR Parsing with Causal Hierarchical Attention and Pointers](https://mlsanity.com/paper/2310.11964/) (2023)
- [Opinion Tree Parsing for Aspect-based Sentiment Analysis](https://mlsanity.com/paper/2306.08925/) (2023)
- [High-order Joint Constituency and Dependency Parsing](https://mlsanity.com/paper/2309.11888/) (2023)
- [Composited-Nested-Learning with Data Augmentation for Nested Named Entity Recognition](https://mlsanity.com/paper/2406.12779/) (2024)
- [Improving Low-Resource Sequence Labeling with Knowledge Fusion and Contextual Label Explanations](https://mlsanity.com/paper/2501.19093/) (2025)
- [Nested Named Entity Recognition as Single-Pass Sequence Labeling](https://mlsanity.com/paper/2505.16855/) (2025)
- [Lexicalized Constituency Parsing for Middle Dutch: Low-resource Training and Cross-Domain Generalization](https://mlsanity.com/paper/2601.07008/) (2026)

## Abstract (arXiv)

Constituency parsing and nested named entity recognition (NER) are similar tasks since they both aim to predict a collection of nested and non-crossing spans. In this work, we cast nested NER to constituency parsing and propose a novel pointing mechanism for bottom-up parsing to tackle both tasks. The key idea is based on the observation that if we traverse a constituency tree in post-order, i.e., visiting a parent after its children, then two consecutively visited spans would share a boundary. Our model tracks the shared boundaries and predicts the next boundary at each step by leveraging a pointer network. As a result, it needs only linear steps to parse and thus is efficient. It also maintains a parsing configuration for structural consistency, i.e., always outputting valid trees. Experimentally, our model achieves the state-of-the-art performance on PTB among all BERT-based models (96.01 F1 score) and competitive performance on CTB7 in constituency parsing; and it also achieves strong performance on three benchmark datasets of nested NER: ACE2004, ACE2005, and GENIA. Our code is publicly available at urlhttps://github.com/sustcsonglin/pointer-net-for-nested.