# FiNER-ORD: Financial Named Entity Recognition Open Research Dataset

arXiv: https://arxiv.org/abs/2302.11157 · HTML: https://mlsanity.com/paper/2302.11157/

## Key facts

- Cited by 17 papers in the map (data through 14 Oct 2026).
- Builds on 11 of its 27 references that are in the map.
- First posted on arXiv 22 Feb 2023.

## Builds on (most cited first, 11 of 11)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [PyTorch: An Imperative Style, High-Performance Deep Learning Library](https://mlsanity.com/paper/1912.01703/) (2019)
- [RoBERTa: A Robustly Optimized BERT Pretraining Approach](https://mlsanity.com/paper/1907.11692/) (2019)
- [Stanza: A Python Natural Language Processing Toolkit for Many Human Languages](https://mlsanity.com/paper/2003.07082/) (2020)
- [LUKE: Deep Contextualized Entity Representations with Entity-aware Self-attention](https://mlsanity.com/paper/2010.01057/) (2020)
- [Dice Loss for Data-imbalanced NLP Tasks](https://mlsanity.com/paper/1911.02855/) (2019)
- [Few-NERD: A Few-Shot Named Entity Recognition Dataset](https://mlsanity.com/paper/2105.07464/) (2021)
- [Automated Concatenation of Embeddings for Structured Prediction](https://mlsanity.com/paper/2010.05006/) (2020)
- [Improving Named Entity Recognition by External Context Retrieving and Cooperative Learning](https://mlsanity.com/paper/2105.03654/) (2021)
- [FiNER: Financial Numeric Entity Recognition for XBRL Tagging](https://mlsanity.com/paper/2203.06482/) (2022)
- [SPot: A tool for identifying operating segments in financial tables](https://mlsanity.com/paper/2005.12966/) (2020)

## Built on by (most cited first, 17 of 17)

- [PIXIU: A Large Language Model, Instruction Data and Evaluation Benchmark for Finance](https://mlsanity.com/paper/2306.05443/) (2023)
- [A Survey of Large Language Models for Financial Applications: Progress, Prospects and Challenges](https://mlsanity.com/paper/2406.11903/) (2024)
- [UniversalNER: Targeted Distillation from Large Language Models for Open Named Entity Recognition](https://mlsanity.com/paper/2308.03279/) (2023)
- [Open-FinLLMs: Open Multimodal Large Language Models for Financial Applications](https://mlsanity.com/paper/2408.11878/) (2024)
- [FinTral: A Family of GPT-4 Level Multimodal Financial Large Language Models](https://mlsanity.com/paper/2402.10986/) (2024)
- [Plutus: Benchmarking Large Language Models in Low-Resource Greek Finance](https://mlsanity.com/paper/2502.18772/) (2025)
- [FinChain: A Symbolic Benchmark for Verifiable Chain-of-Thought Financial Reasoning](https://mlsanity.com/paper/2506.02515/) (2025)
- [Zero is Not Hero Yet: Benchmarking Zero-Shot Performance of LLMs for Financial Tasks](https://mlsanity.com/paper/2305.16633/) (2023)
- [FinEntity: Entity-level Sentiment Classification for Financial Texts](https://mlsanity.com/paper/2310.12406/) (2023)
- [No Language is an Island: Unifying Chinese and English in Financial Large Language Models, Instruction Data, and Benchmarks](https://mlsanity.com/paper/2403.06249/) (2024)
- [The CLEF-2026 FinMMEval Lab: Multilingual and Multimodal Evaluation of Financial AI Systems](https://mlsanity.com/paper/2602.10886/) (2026)
- [Cross-LLM Consistency in Inference: Evidence from Shared Interactions](https://mlsanity.com/paper/2606.08129/) (2026)
- [Reliable Financial Named Entity Recognition Under Domain Shift: Confidence Estimation and Selective Prediction](https://mlsanity.com/paper/2608.19558/) (2026)
- [Malaysian English News Decoded: A Linguistic Resource for Named Entity and Relation Extraction](https://mlsanity.com/paper/2402.14521/) (2024)
- [Who Is the Story About? Protagonist Entity Recognition in News](https://mlsanity.com/paper/2511.07296/) (2025)
- [Is GPT-OSS All You Need? Benchmarking Large Language Models for Financial Intelligence and the Surprising Efficiency Paradox](https://mlsanity.com/paper/2512.14717/) (2025)
- [A Hybrid Method for Low-Resource Named Entity Recognition](https://mlsanity.com/paper/2605.04489/) (2026)

## Abstract (arXiv)

Over the last two decades, the development of the CoNLL-2003 named entity recognition (NER) dataset has helped enhance the capabilities of deep learning and natural language processing (NLP). The finance domain, characterized by its unique semantic and lexical variations for the same entities, presents specific challenges to the NER task; thus, a domain-specific customized dataset is crucial for advancing research in this field. In our work, we develop the first high-quality English Financial NER Open Research Dataset (FiNER-ORD). We benchmark multiple pre-trained language models (PLMs) and large-language models (LLMs) on FiNER-ORD. We believe our proposed FiNER-ORD dataset will open future opportunities to use FiNER-ORD as a benchmark for financial domain-specific NER and NLP tasks. Our dataset, models, and code are publicly available on GitHub and Hugging Face under CC BY-NC 4.0 license.