# NEREL: A Russian Dataset with Nested Named Entities, Relations and Events

arXiv: https://arxiv.org/abs/2108.13112 · HTML: https://mlsanity.com/paper/2108.13112/

## Key facts

- Cited by 13 papers in the map (data through 14 Oct 2026).
- Builds on 14 of its 36 references that are in the map.
- First posted on arXiv 30 Aug 2021.

## Builds on (most cited first, 14 of 14)

- [SpanBERT: Improving Pre-training by Representing and Predicting Spans](https://mlsanity.com/paper/1907.10529/) (2019)
- [K-BERT: Enabling Language Representation with Knowledge Graph](https://mlsanity.com/paper/1909.07606/) (2019)
- [DocRED: A Large-Scale Document-Level Relation Extraction Dataset](https://mlsanity.com/paper/1906.06127/) (2019)
- [Advances in Pre-Training Distributed Word Representations](https://mlsanity.com/paper/1712.09405/) (2017)
- [A Unified MRC Framework for Named Entity Recognition](https://mlsanity.com/paper/1910.11476/) (2019)
- [Named Entity Recognition as Dependency Parsing](https://mlsanity.com/paper/2005.07150/) (2020)
- [Adaptation of Deep Bidirectional Multilingual Transformers for Russian Language](https://mlsanity.com/paper/1905.07213/) (2019)
- [TACRED Revisited: A Thorough Evaluation of the TACRED Relation Extraction Task](https://mlsanity.com/paper/2004.14855/) (2020)
- [Knowledge Graph-Augmented Abstractive Summarization with Semantic-Driven Cloze Reward](https://mlsanity.com/paper/2005.01159/) (2020)
- [OpenNRE: An Open and Extensible Toolkit for Neural Relation Extraction](https://mlsanity.com/paper/1909.13078/) (2019)
- [NNE: A Dataset for Nested Named Entity Recognition in English Newswire](https://mlsanity.com/paper/1906.01359/) (2019)
- [Improving Relation Extraction by Pre-trained Language Representations](https://mlsanity.com/paper/1906.03088/) (2019)
- [DaN+: Danish Nested Named Entities and Lexical Normalization](https://mlsanity.com/paper/2105.11301/) (2021)
- [A Finnish News Corpus for Named Entity Recognition](https://mlsanity.com/paper/1908.04212/) (2019)

## Built on by (most cited first, 13 of 13)

- [NEREL-BIO: A Dataset of Biomedical Abstracts Annotated with Nested Named Entities](https://mlsanity.com/paper/2210.11913/) (2022)
- [RuNNE-2022 Shared Task: Recognizing Nested Named Entities](https://mlsanity.com/paper/2205.11159/) (2022)
- [MOLE: Metadata Extraction and Validation in Scientific Papers Using LLMs](https://mlsanity.com/paper/2505.19800/) (2025)
- [RuSentNE-2023: Evaluating Entity-Oriented Sentiment Analysis on Russian News Texts](https://mlsanity.com/paper/2305.17679/) (2023)
- [RaguTeam at SemEval-2026 Task 8: Meno and Friends in a Judge-Orchestrated LLM Ensemble for Faithful Multi-Turn Response Generation](https://mlsanity.com/paper/2605.04523/) (2026)
- [Few-Shot Nested Named Entity Recognition](https://mlsanity.com/paper/2212.00953/) (2022)
- [Cross-lingual Named Entity Corpus for Slavic Languages](https://mlsanity.com/paper/2404.00482/) (2024)
- [TERMinator: A system for scientific texts processing](https://mlsanity.com/paper/2209.14854/) (2022)
- [RAGU: A Multi-Step GraphRAG Engine with a Compact Domain-Adapted LLM](https://mlsanity.com/paper/2607.11683/) (2026)
- [Razmecheno: Named Entity Recognition from Digital Archive of Diaries "Prozhito"](https://mlsanity.com/paper/2201.09997/) (2022)
- [Learning Nested Named Entity Recognition from Flat Annotations](https://mlsanity.com/paper/2603.00840/) (2026)
- [WhoSaidIt: Human-LLM Collaborative Annotation for Text-Based Multilingual Speaker-Attribute Classification](https://mlsanity.com/paper/2605.26070/) (2026)
- [When Harness Beats Scale, and When Reading Beats Both](https://mlsanity.com/paper/2609.34366/) (2026)

## Abstract (arXiv)

In this paper, we present NEREL, a Russian dataset for named entity recognition and relation extraction. NEREL is significantly larger than existing Russian datasets: to date it contains 56K annotated named entities and 39K annotated relations. Its important difference from previous datasets is annotation of nested named entities, as well as relations within nested entities and at the discourse level. NEREL can facilitate development of novel models that can extract relations between nested named entities, as well as relations on both sentence and document levels. NEREL also contains the annotation of events involving named entities and their roles in the events. The NEREL collection is available via https://github.com/nerel-ds/NEREL.