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Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
To better tackle the named entity recognition (NER) problem on languages with little/no labeled data, cross-lingual NER must effectively leverage knowledge learned from source languages with rich labeled data. Previous works on cross-lingual NER are mostly based on label projection with pairwise texts or direct model transfer. However, such methods either are not applicable if the labeled data in the source languages is unavailable, or do not leverage information contained in unlabeled data indoi:10.18653/v1/2020.acl-main.581 fatcat:c2ttemiwq5csjewpgzafcnrtyq