# Multilingual End to End Entity Linking

arXiv: https://arxiv.org/abs/2306.08896 · HTML: https://mlsanity.com/paper/2306.08896/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- Builds on 28 of its 51 references that are in the map.
- First posted on arXiv 15 Jun 2023.

## Builds on (most cited first, 28 of 28)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Billion-scale similarity search with GPUs](https://mlsanity.com/paper/1702.08734/) (2017)
- [Cross-lingual Language Model Pretraining](https://mlsanity.com/paper/1901.07291/) (2019)
- [Autoregressive Entity Retrieval](https://mlsanity.com/paper/2010.00904/) (2020)
- [Knowledge Enhanced Contextual Word Representations](https://mlsanity.com/paper/1909.04164/) (2019)
- [Zero-Shot Entity Linking by Reading Entity Descriptions](https://mlsanity.com/paper/1906.07348/) (2019)
- [End-to-End Neural Entity Linking](https://mlsanity.com/paper/1808.07699/) (2018)
- [Scalable Zero-shot Entity Linking with Dense Entity Retrieval](https://mlsanity.com/paper/1911.03814/) (2019)
- [Deep Joint Entity Disambiguation with Local Neural Attention](https://mlsanity.com/paper/1704.04920/) (2017)
- [Efficient One-Pass End-to-End Entity Linking for Questions](https://mlsanity.com/paper/2010.02413/) (2020)
- [ReFinED: An Efficient Zero-shot-capable Approach to End-to-End Entity Linking](https://mlsanity.com/paper/2207.04108/) (2022)
- [Entity Linking in 100 Languages](https://mlsanity.com/paper/2011.02690/) (2020)
- [Multilingual Autoregressive Entity Linking](https://mlsanity.com/paper/2103.12528/) (2021)
- [Investigating Entity Knowledge in BERT with Simple Neural End-To-End Entity Linking](https://mlsanity.com/paper/2003.05473/) (2020)
- [DeepType: Multilingual Entity Linking by Neural Type System Evolution](https://mlsanity.com/paper/1802.01021/) (2018)
- [Fine-Grained Entity Typing for Domain Independent Entity Linking](https://mlsanity.com/paper/1909.05780/) (2019)
- [Joint Learning of Named Entity Recognition and Entity Linking](https://mlsanity.com/paper/1907.08243/) (2019)
- [Highly Parallel Autoregressive Entity Linking with Discriminative Correction](https://mlsanity.com/paper/2109.03792/) (2021)
- [Empirical Evaluation of Pretraining Strategies for Supervised Entity Linking](https://mlsanity.com/paper/2005.14253/) (2020)
- [Neural Cross-Lingual Entity Linking](https://mlsanity.com/paper/1712.01813/) (2017)
- [Simple Question Answering by Attentive Convolutional Neural Network](https://mlsanity.com/paper/1606.03391/) (2016)
- [Zero-shot Neural Transfer for Cross-lingual Entity Linking](https://mlsanity.com/paper/1811.04154/) (2018)
- [Improving Candidate Generation for Low-resource Cross-lingual Entity Linking](https://mlsanity.com/paper/2003.01343/) (2020)
- [Learning to Generate Wikipedia Summaries for Underserved Languages from Wikidata](https://mlsanity.com/paper/1803.07116/) (2018)
- [Joint Multilingual Supervision for Cross-lingual Entity Linking](https://mlsanity.com/paper/1809.07657/) (2018)
- [One for All: Towards Language Independent Named Entity Linking](https://mlsanity.com/paper/1712.01797/) (2017)
- [Towards Zero-resource Cross-lingual Entity Linking](https://mlsanity.com/paper/1909.13180/) (2019)
- [Scalable graph-based individual named entity identification](https://mlsanity.com/paper/1811.10547/) (2018)

## Built on by (most cited first, 8 of 8)

- [PyThaiNLP: Thai Natural Language Processing in Python](https://mlsanity.com/paper/2312.04649/) (2023)
- [LLM-Independent Adaptive RAG: Let the Question Speak for Itself](https://mlsanity.com/paper/2505.04253/) (2025)
- [Konstruktor: A Strong Baseline for Simple Knowledge Graph Question Answering](https://mlsanity.com/paper/2409.15902/) (2024)
- [Musical Heritage Historical Entity Linking](https://mlsanity.com/paper/2502.09168/) (2025)
- [MERLIN: A Testbed for Multilingual Multimodal Entity Recognition and Linking](https://mlsanity.com/paper/2510.14307/) (2025)
- [It's All About the Confidence: An Unsupervised Approach for Multilingual Historical Entity Linking using Large Language Models](https://mlsanity.com/paper/2601.08500/) (2026)
- [ENEIDE: A High Quality Silver Standard Dataset for Named Entity Recognition and Linking in Historical Italian](https://mlsanity.com/paper/2603.29801/) (2026)
- [Beyond Single-Negative Preference: Multi-Negative DPO for LLM-Centric Historical Entity Linking](https://mlsanity.com/paper/2609.07379/) (2026)

## Abstract (arXiv)

Entity Linking is one of the most common Natural Language Processing tasks in practical applications, but so far efficient end-to-end solutions with multilingual coverage have been lacking, leading to complex model stacks. To fill this gap, we release and open source BELA, the first fully end-to-end multilingual entity linking model that efficiently detects and links entities in texts in any of 97 languages. We provide here a detailed description of the model and report BELA's performance on four entity linking datasets covering high- and low-resource languages.