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2022 EMNLP EMNLP 2022

Zero-shot Cross-Language Transfer of Monolingual Entity Linking Models

AbstractMost entity linking systems, whether mono or multilingual, link mentions to a single English knowledge base. Few have considered linking non-English text to a non-English KB, and therefore, transferring an English entity linking model to both a new document and KB language. We consider the task of zero-shot cross-language transfer of entity linking systems to a new language and KB. We find that a system trained with multilingual representations does reasonably well, and propose improvements to system training that lead to improved recall in most datasets, often matching the in-language performance. We further conduct a detailed evaluation to elucidate the challenges of this setting.

🌉 Interdisciplinary Bridge - Artificial Intelligence and Natural Language Processing

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