Cross-lingual Extended Named Entity Classification of Wikipedia Articles

• URL: http://arxiv.org/abs/2010.03424v2
• Date: Sat, 17 Oct 2020 09:06:42 GMT
• Title: Cross-lingual Extended Named Entity Classification of Wikipedia Articles
• Authors: The Viet Bui, Phuong Le-Hong
• Abstract summary: This paper describes our method to solving the problem and discusses the official results. We propose a three-stage approach including multilingual model pre-training, monolingual model fine-tuning and cross-lingual voting. Our system is able to achieve the best scores for 25 out of 30 languages; and its accuracy gaps to the best performing systems of the other five languages are relatively small.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The FPT.AI team participated in the SHINRA2020-ML subtask of the NTCIR-15 SHINRA task. This paper describes our method to solving the problem and discusses the official results. Our method focuses on learning cross-lingual representations, both on the word level and document level for page classification. We propose a three-stage approach including multilingual model pre-training, monolingual model fine-tuning and cross-lingual voting. Our system is able to achieve the best scores for 25 out of 30 languages; and its accuracy gaps to the best performing systems of the other five languages are relatively small.

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