NLP

Multilingual End to End Entity Linking

June 15, 2023

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 lowresource languages.

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AUTHORS

Written by

Mike Plekhanov

Nora Kassner

Kashyap Popat

Louis Martin

Simone Merello

Borislav Kozlovskii

Frederic Dreyer

Nicola Cancedda

Publisher

https://arxiv.org/

Research Topics

Natural Language Processing (NLP)

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