Elamur Research⌕
☰
home / papers / 2026 / entity-linkings: A Unified Library for Entity Linking

entity-linkings: A Unified Library for Entity Linking

Paper · 2026 · Yuya Sawada, Tsuyoshi Fujita, Yusuke Sakai et al.

Summary

Entity linking (EL) research suffers from poor reproducibility. Many official implementations are missing or abandoned, and even systems built on the same Wikidata dump differ in dump date, candidate pruning and data formats. As a result, papers often copy baseline scores from earlier work instead of rerunning them. The NAIST authors respond with entity-linkings, an open-source Python package (MIT license, on PyPI and GitHub) usable through both a CLI and a Python API.

The library splits an EL system into three interchangeable modules:

  • Mention Detector: off-the-shelf NER such as spaCy.
  • Candidate Generator: lexical retrievers or embedding-based retrievers.
  • Candidate Reranker: encoder-only, encoder-decoder, or LLM-based models.

Any generator can be combined with any reranker, and the main focus is entity disambiguation.

Replication runs on ZELDA (disambiguation) and GERBIL (end-to-end linking) gave scores consistent with previously published results for three retrievers and five rerankers. Simple pipelines assembled with little code proved reasonably competitive. The toolkit therefore offers a common basis for fair comparison and for developing new methods.

Key points

  • Modules and models: retrievers include BM25, the Zelda Candidate List, Dual-Encoder (BERT Base) and Text Embedding (E5 Base). Rerankers include FEVRY, Cross-Encoder (BLINK-style), ExtEnD (Longformer Base), FusionED (FlanT5 small) and ChatEL (GPT-4o mini).
  • Metrics: Recall@k for candidate generation, Top-1 accuracy for reranking, and InKB micro-F1 for end-to-end EL.
  • ZELDA benchmark: about 95k training documents, an 82.2k-entity vocabulary, and nine test sets (AIDA-B, TWEEKI, Reddit, WNED, ShadowLinks).
  • GERBIL results: the system is trained on AIDA-CoNLL, with mentions detected by spaCy. Adding Cross-Encoder or ExtEnD on top of Dual-Encoder improved F1 (e.g., MSNBC: 0.437 → 0.474 / 0.472). FEVRY dropped sharply (0.146), probably because it ignores entity titles and descriptions. ReFinED, trained with external resources, reached 0.561.
  • Planned extensions: end-to-end EL architectures and retriever-reader models, partly to reduce errors from spaCy mention detection.

Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.

 Institutions

🎓Nara Institute of Science and TechnologyIkoma · Japan46 works · 4,565 citations

 Fields, topics and concepts

📚 Shelves 5The field of science this work belongs to (OpenAlex fields).Computer Science · 16,667 worksArtificial Intelligence · 16,194 worksArts and Humanities · 16,039 worksLanguage and Linguistics · 15,891 worksComputer Vision and Pattern Recognition · 2,869 works

🧭 Topics 1Research subjects and languages the work is about.Named entity recognition · 200 works

Cite

Cite as Yuya Sawada, Tsuyoshi Fujita, Yusuke Sakai and Taro Watanabe. 2026. entity-linkings: A Unified Library for Entity Linking. Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 3: System Demonstrations).

The paper itself, not this page. BibTeX from the library's record of the work. DOI 10.18653/v1/2026.eacl-demo.42

@inproceedings{sawada2026entity,
  title = {{entity-linkings: A Unified Library for Entity Linking}},
  author = {Yuya Sawada, Tsuyoshi Fujita, Yusuke Sakai and Taro Watanabe},
  booktitle = {Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 3: System Demonstrations)},
  year = {2026},
  doi = {10.18653/v1/2026.eacl-demo.42},
  url = {https://doi.org/10.18653/v1/2026.eacl-demo.42}
}

References

36 references, 3 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

  1. Alan Akbik, Duncan Blythe, and Roland Vollgraf. 2018. Contextual string embeddings for sequence labeling. In Proceedings of the 27th International Conference on Computational Linguistics, pages 1638– 1649, Santa Fe, New Mexico, USA. Association for Computational Linguistics.
  2. Tom Ayoola, Shubhi Tyagi, Joseph Fisher, Christos Christodoulopoulos, and Andrea Pierleoni. 2022. Re-FinED: An efficient zero-shot-capable approach to end-to-end entity linking. In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Huma… find
  3. Edoardo Barba, Luigi Procopio, and Roberto Navigli. 2022. ExtEnD: Extractive entity disambiguation. In https://www.aclweb.org/adminwiki/index.php/ ACL_Policy_on_Publication_Ethics Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 2… ↗
  4. Nicholas Botzer, Yifan Ding, and Tim Weninger. 2021. Reddit entity linking dataset. Inf. Process. Manage., 58(3). find
  5. Nicola De Cao, Gautier Izacard, Sebastian Riedel, and Fabio Petroni. 2021. Autoregressive entity retrieval. In International Conference on Learning Representations. find
  6. Silviu Cucerzan. 2007. Large-scale named entity disambiguation based on Wikipedia data. In Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL), pages 708–716, Prague, Czech Republic. Association for Co… find
  7. Hiroyuki Deguchi, Yusuke Sakai, Hidetaka Kamigaito, and Taro Watanabe. 2024. mbrs: A library for minimum Bayes risk decoding. In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, pages 351–362, Miami, Florida, USA. Association for Computat… find
  8. Leon Derczynski, Diana Maynard, Giuseppe Rizzo, Marieke van Erp, Genevieve Gorrell, Raphaël Troncy, Johann Petrak, and Kalina Bontcheva. 2015. Analysis of named entity recognition and linking for tweets. Information Processing & Management, 51(2):32– 49. find
  9. Yifan Ding, Qingkai Zeng, and Tim Weninger. 2024. ChatEL: Entity linking with chatbots. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 3086–3097, Torino, Italia. ELRA and ICCL. find
  10. Yotam Eshel, Noam Cohen, Kira Radinsky, Shaul Markovitch, Ikuya Yamada, and Omer Levy. 2017. Named entity disambiguation for noisy text. In Proceedings of the 21st Conference on Computational Natural Language Learning (CoNLL 2017), pages 58–68, Vancouver, Canada. Association for Computational Lingui… find
  11. Thibault Févry, Nicholas FitzGerald, Livio Baldini Soares, and Tom Kwiatkowski. 2020. Empirical evaluation of pretraining strategies for supervised entity linking. Preprint, arXiv:2005.14253. — [arXiv:2005.14253](https://arxiv.org/abs/2005.14253) find
  12. Pierre-Yves Genest, Pierre-Edouard Portier, Elöd Egyed-Zsigmond, and Martino Lovisetto. 2023. Linked-DocRED – Enhancing DocRED with Entity-Linking to Evaluate End-To-End Document-Level Information Extraction Pipelines. In Proceedings of the 46th International ACM SIGIR Conference on Research and Dev… find
  13. Daniel Gillick, Sayali Kulkarni, Larry Lansing, Alessandro Presta, Jason Baldridge, Eugene Ie, and Diego Garcia-Olano. 2019. Learning dense representations for entity retrieval. In Proceedings of the 23rd Conference on Computational Natural Language Learning (CoNLL), pages 528–537, Hong Kong, China.…
  14. Takumi Goto, Yusuke Sakai, and Taro Watanabe. 2025. gec-metrics: A unified library for grammatical error correction evaluation. In Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations), pages 524–534, Vienna, Austria. Association fo… find
  15. Zhaochen Guo and Denilson Barbosa. 2014. Robust entity linking via random walks. In Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management, CIKM 2014, Shanghai, China, November 3-7, 2014, pages 499–508. find
  16. Zhaochen Guo and Denilson Barbosa. 2018. Robust named entity disambiguation with random walks. Semant. Web, 9(4):459–479. find
  17. Bahareh Harandizadeh and Sameer Singh. 2020. Tweeki: Linking named entities on Twitter to a knowledge graph. In Proceedings of the Sixth Workshop on Noisy User-generated Text (W-NUT 2020), pages 222–231, Online. Association for Computational Linguistics. find
  18. Johannes Hoffart, Stephan Seufert, Dat Ba Nguyen, Martin Theobald, and Gerhard Weikum. 2012. Kore: keyphrase overlap relatedness for entity disambiguation. In Proceedings of the 21st ACM International Conference on Information and Knowledge Management, CIKM ’12, page 545–554, New York, NY, USA. Asso… find
  19. Johannes Hoffart, Mohamed Amir Yosef, Ilaria Bordino, Hagen Fürstenau, Manfred Pinkal, Marc Spaniol, Bilyana Taneva, Stefan Thater, and Gerhard Weikum. 2011. Robust disambiguation of named entities in text. In Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing, pa… find
  20. Matthew Honnibal, Ines Montani, Sofie Van Lan-deghem, and Adriane Boyd. 2020. spaCy: Industrial-strength Natural Language Processing in Python. find
  21. Lajanugen Logeswaran, Ming-Wei Chang, Kenton Lee, Kristina Toutanova, Jacob Devlin, and Honglak Lee. 2019. Zero-shot entity linking by reading entity descriptions. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 3449–3460, Florence, Italy. Associatio… find
  22. Xing Han Lù. 2024. Bm25s: Orders of magnitude faster lexical search via eager sparse scoring. Preprint, arXiv:2407.03618. — [arXiv:2407.03618](https://arxiv.org/abs/2407.03618) find
  23. Marcel Milich and Alan Akbik. 2023. ZELDA: A comprehensive benchmark for supervised entity disambiguation. In Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics, pages 2061–2072, Dubrovnik, Croatia. Association for Computational Linguistics. find
  24. David Milne and Ian H. Witten. 2008. Learning to link with wikipedia. In Proceedings of the 17th ACM Conference on Information and Knowledge Management, CIKM ’08, page 509–518, New York, NY, USA. Association for Computing Machinery. find
  25. Andrea Giovanni Nuzzolese, Anna Lisa Gentile, Valentina Presutti, Aldo Gangemi, Darío Garigliotti, and Roberto Navigli. 2015. Open knowledge extraction challenge. In Semantic Web Evaluation Challenges, pages 3–15. Springer. find
  26. Andrea Giovanni Nuzzolese, Anna Lisa Gentile, Valentina Presutti, Aldo Gangemi, Robert Meusel, and Heiko Paulheim. 2016. The second open knowledge extraction challenge. In Semantic Web Challenges, pages 3–16, Cham. Springer International Publishing. find
  27. Yasumasa Onoe and Greg Durrett. 2020. Fine-grained entity typing for domain independent entity linking. Proceedings of the AAAI Conference on Artificial Intelligence, 34(05):8576–8583. find
  28. Maria Pershina, Yifan He, and Ralph Grishman. 2015. Personalized page rank for named entity disambiguation. In Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 238–243, Denver, Colorado. Association… find
  29. Fabio Petroni, Aleksandra Piktus, Angela Fan, Patrick Lewis, Majid Yazdani, Nicola De Cao, James Thorne, Yacine Jernite, Vladimir Karpukhin, Jean Maillard, Vassilis Plachouras, Tim Rocktäschel, and Sebastian Riedel. 2021. KILT: a benchmark for knowledge intensive language tasks. In Proceedings of th…
  30. Vera Provatorova, Samarth Bhargav, Svitlana Vakulenko, and Evangelos Kanoulas. 2021. Robustness evaluation of entity disambiguation using prior probes: the case of entity overshadowing. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pages 10501–10510, Onli… find
  31. Lev Ratinov, Dan Roth, Doug Downey, and Mike Anderson. 2011. Local and global algorithms for disambiguation to Wikipedia. In Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, pages 1375–1384, Portland, Oregon, USA. Association for C… find
  32. Michael Röder, Ricardo Usbeck, Sebastian Hellmann, Daniel Gerber, and Andreas Both. 2014. N 3 - a collection of datasets for named entity recognition and disambiguation in the NLP interchange format. In Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC’14),… find
  33. Susanna Rücker and Alan Akbik. 2025. Evaluating design decisions for dual encoder-based entity disambiguation. In Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 15685–15701, Vienna, Austria. Association for Computational Linguis… find
  34. Michael Röder, Ricardo Usbeck, and Axel-Cyrille Ngonga Ngomo. 2018. GERBIL -Benchmarking Named Entity Recognition and Linking consistently. Semantic Web, 9(5):605–625. find
  35. Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 6397–6407, Online. Association for Computational Linguistics. find
  36. Wenzheng Zhang, Wenyue Hua, and Karl Stratos. 2022. EntQA: Entity linking as question answering. In International Conference on Learning Representations. find

Updated

↑ back to top

This page in Markdown → https://md.research.elamur.ai/free/en/papers/sawada-2026-entity-linkings-unified-library-entity/