在Twitter上标注挪威语变体的词性
Annotating Norwegian Language Varieties on Twitter for Part-of-Speech
摘要：
挪威Twitter数据对自然语言处理（NLP）任务提出了一个有趣的挑战。这些文本对于在两种挪威书面形式（Bokmål和Nynorsk）之一的标准化文本上训练的模型来说是困难的，因为它们包含社交媒体文本的典型变体以及大量的方言变体。在本文中，我们提出了一个新的挪威Twitter数据集与POS标签注释。我们发现，在通用依赖（UD）数据上训练的模型在针对该数据集进行评估时表现较差，而在Bokmål上训练的模型通常比在Nynorsk上训练的模型表现更好。我们还看到，方言推文的性能与某些模型的书面标准相当。最后，我们对模型通常在这些数据上产生的错误进行了详细的分析。
英文摘要：
Norwegian Twitter data poses an interesting challenge for Natural Language Processing (NLP) tasks. These texts are difficult for models trained on standardized text in one of the two Norwegian written forms (Bokmål and Nynorsk), as they contain both the typical variation of social media text, as well as a large amount of dialectal variety. In this paper we present a novel Norwegian Twitter dataset annotated with POS-tags. We show that models trained on Universal Dependency (UD) data perform worse when evaluated against this dataset, and that models trained on Bokmål generally perform better than those trained on Nynorsk. We also see that performance on dialectal tweets is comparable to the written standards for some models. Finally we perform a detailed analysis of the errors that models commonly make on this data.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
