Resources and Evaluations for Danish Entity Resolution

Maria Barrett, Hieu Lam, Martin Wu, Ophélie Lacroix, Barbara Plank, Anders Søgaard
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引用次数: 1

Abstract

Automatic coreference resolution is understudied in Danish even though most of the Danish Dependency Treebank (Buch-Kromann, 2003) is annotated with coreference relations. This paper describes a conversion of its partial, yet well-documented, coreference relations into coreference clusters and the training and evaluation of coreference models on this data. To the best of our knowledge, these are the first publicly available, neural coreference models for Danish. We also present a new entity linking annotation on the dataset using WikiData identifiers, a named entity disambiguation (NED) dataset, and a larger automatically created NED dataset enabling wikily supervised NED models. The entity linking annotation is benchmarked using a state-of-the-art neural entity disambiguation model.
丹麦实体决议的资源和评价
尽管大多数丹麦依赖树库(Buch-Kromann, 2003)都标注了共引用关系,但丹麦语对自动共引用解析的研究还不够充分。本文描述了将其部分但有充分记录的共参考关系转换为共参考簇以及在此数据上的共参考模型的训练和评估。据我们所知,这些是第一个公开可用的,丹麦人的神经共参考模型。我们还使用WikiData标识符在数据集上提供了一个新的实体链接注释,一个命名实体消歧(NED)数据集,以及一个更大的自动创建的NED数据集,支持WikiData监督NED模型。实体链接注释使用最先进的神经实体消歧模型进行基准测试。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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