论文标题
丹麦的命名实体识别的神经跨语性转移和有限的注释数据
Neural Cross-Lingual Transfer and Limited Annotated Data for Named Entity Recognition in Danish
论文作者
论文摘要
命名实体识别（NER）通过引入深度神经体系结构大大推进。但是，这些方法的成功取决于大量培训数据。与丹麦的情况一样，公开可公开的人类标签数据集的稀缺性导致对现有NER系统的评估有限。本文研究了丹麦跨语言转移的有效性，评估了其对有限的黄金数据的互补性，并阐明了丹麦Ner的性能。
Named Entity Recognition (NER) has greatly advanced by the introduction of deep neural architectures. However, the success of these methods depends on large amounts of training data. The scarcity of publicly-available human-labeled datasets has resulted in limited evaluation of existing NER systems, as is the case for Danish. This paper studies the effectiveness of cross-lingual transfer for Danish, evaluates its complementarity to limited gold data, and sheds light on performance of Danish NER.
