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Multilingual End to End Entity Linking

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arxiv 2306.08896 v1 pith:WB7P64JI submitted 2023-06-15 cs.CL

Mikhail Plekhanov , Nora Kassner , Kashyap Popat , Louis Martin , Simone Merello , Borislav Kozlovskii , Frédéric A. Dreyer , Nicola Cancedda This is my paper · ORCID
classification cs.CL
keywords entitylinkingmodelmultilingualbelaend-to-endlanguagesapplications
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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.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. LLM-Independent Adaptive RAG: Let the Question Speak for Itself

    cs.CL 2025-05 conditional novelty 6.0 of 10

    External features such as entity popularity and question type can drive adaptive retrieval decisions without extra large-language-model calls, matching the accuracy of uncertainty-based methods on several QA benchmark...

  2. Musical Heritage Historical Entity Linking

    cs.CL 2025-02 conditional novelty 6.0 of 10

    MHERCL, a gold-standard dataset of 875 sentences from 19th-century music periodicals, shows that type and time filtering plus NIL-aware heuristics improve entity linking over off-the-shelf models and LLMs.

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