Multilingual End to End Entity Linking

Mikhail Plekhanov; Nora Kassner; Kashyap Popat; Louis Martin; Simone Merello; Borislav Kozlovskii; Frédéric A. Dreyer; Nicola Cancedda

arXiv · 2306.08896

Multilingual End to End Entity Linking

Mikhail Plekhanov·Nora Kassner·Kashyap Popat·Louis Martin·Simone Merello·Borislav Kozlovskii·Frédéric A. Dreyer·Nicola Cancedda

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Abstract

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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Mikhail Plekhanov, Nora Kassner, Kashyap Popat, Louis Martin, Simone Merello, Borislav Kozlovskii, Frédéric A. Dreyer, Nicola Cancedda. 2023-06-15. Multilingual End to End Entity Linking. https://arxiv.org/abs/2306.08896

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