Mahānāma: A Unique Testbed for Literary Entity Discovery and Linking (2025.emnlp-main)
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| Challenge: | High lexical variation, ambiguous references, and long-range dependencies make entity resolution in literary texts particularly challenging. |
| Approach: | They present a large-scale dataset for end-to-end Entity Discovery and Linking (EDL) in Sanskrit. |
| Outcome: | The proposed dataset is aligned with an English knowledge base to support cross-lingual linking. |
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| Challenge: | Existing approaches to multilingual entity linking are cross-lingual, with a focus on zero-shot evaluation. |
| Approach: | They propose a new formulation for multilingual entity linking where language-specific mentions resolve to a language-agnostic Knowledge Base. |
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MERLIN: A Testbed for Multilingual Multimodal Entity Recognition and Linking (2026.tacl-1)
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Sathyanarayanan Ramamoorthy, Vishwa Shah, Simran Khanuja, Zaid Sheikh, Shan Jie, Ann Chia, Shearman Chua, Graham Neubig
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mReFinED: An Efficient End-to-End Multilingual Entity Linking System (2023.findings-emnlp)
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| Challenge: | Existing work assumed that entity mentions were given and skipped the entity mention detection step due to a lack of high-quality multilingual training corpora. |
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An annotated dataset of literary entities (N19-1)
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| Challenge: | Existing datasets built on news focus on non-named entities, but not literary texts. |
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| Challenge: | Entity linking (EL) focuses on associating ambiguous mentions in text with corresponding entities in a knowledge graph. |
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| Challenge: | Existing work on Entity Linking assumes that the knowledge base is complete and all mentions can be linked. |
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ZELDA: A Comprehensive Benchmark for Supervised Entity Disambiguation (2023.eacl-main)
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| Challenge: | Entity disambiguation (ED) is the task of disambiguating named entity mentions in text to unique entries in a knowledge base. |
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ELISA-EDL: A Cross-lingual Entity Extraction, Linking and Localization System (N18-5)
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| Challenge: | ELISA-EDL is a cross-lingual entity extraction, linking and localization system for Wikipedia languages. |
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| Challenge: | Existing coreference resolution datasets are either small in scale or restrict coreference to a limited text span. |
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COMETA: A Corpus for Medical Entity Linking in the Social Media (2020.emnlp-main)
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| Challenge: | Existing datasets for Entity Linking (EL) fail to address the complex nature of health terminology in layman’s language. |
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