Cross-Lingual Transfer in Zero-Shot Cross-Language Entity Linking

• URL: http://arxiv.org/abs/2010.09828v2
• Date: Wed, 7 Jul 2021 19:44:49 GMT
• Title: Cross-Lingual Transfer in Zero-Shot Cross-Language Entity Linking
• Authors: Elliot Schumacher, James Mayfield, Mark Dredze
• Abstract summary: Cross-language entity linking grounds mentions in multiple languages to a single-language knowledge base. We find that the multilingual ability of BERT leads to robust performance in monolingual and multilingual settings.
• Score: 19.083300046605252
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Cross-language entity linking grounds mentions in multiple languages to a single-language knowledge base. We propose a neural ranking architecture for this task that uses multilingual BERT representations of the mention and the context in a neural network. We find that the multilingual ability of BERT leads to robust performance in monolingual and multilingual settings. Furthermore, we explore zero-shot language transfer and find surprisingly robust performance. We investigate the zero-shot degradation and find that it can be partially mitigated by a proposed auxiliary training objective, but that the remaining error can best be attributed to domain shift rather than language transfer.

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