FRINK Linked Data Fragments server

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• W3100843744 abstract "We propose a new formulation for multilingual entity linking, where language-specific mentions resolve to a language-agnostic Knowledge Base. We train a dual encoder in this new setting, building on prior work with improved feature representation, negative mining, and an auxiliary entity-pairing task, to obtain a single entity retrieval model that covers 100+ languages and 20 million entities. The model outperforms state-of-the-art results from a far more limited cross-lingual linking task. Rare entities and low-resource languages pose challenges at this large-scale, so we advocate for an increased focus on zero- and few-shot evaluation. To this end, we provide Mewsli-9, a large new multilingual dataset matched to our setting, and show how frequency-based analysis provided key insights for our model and training enhancements." @default.
• W3100843744 created "2020-11-23" @default.
• W3100843744 creator A5006082185 @default.
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• W3100843744 date "2020-01-01" @default.
• W3100843744 modified "2023-10-17" @default.
• W3100843744 title "Entity Linking in 100 Languages" @default.
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• W3100843744 doi "https://doi.org/10.18653/v1/2020.emnlp-main.630" @default.
• W3100843744 hasPublicationYear "2020" @default.
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