语法复杂性在二语习得中受到广泛关注。尽管已经开发了计算工具来分析语法复杂性，大多数相关研究在英语作为第二语言的背景下调查了这种结构。为了应对越来越多的二语汉语学习者，扩展对二语语法复杂性的研究具有重要意义。推动相关研究,我们评估了新的计算工具，Stanza,二语写作词性标注的准确性。我们特别关注与二语汉语发展密切相关的八个语法特征。然后，我们报告了精确度，Recalls,和个体语法特征的F分数，并对系统标记错误进行了定性分析。在精度方面，三个特征有很高的比率，超过90%(即，巴和贝的标记，分类器,-de作为名词修饰符标记)。为了召回，四个特征有很高的比率，超过90%(即，方面标记,巴和贝的标记，分类器,-de作为名词修饰符标记)。总的来说,根据F分数，Stanza在ba和bei标记上有很好的标记性能，分类器,和-de作为名词修饰符标记。此评估为计划使用此计算工具研究第二语言习得或一般应用语言学中的二语汉语发展的学者提供了研究意义。
Grammatical complexity has received extensive attention in second language acquisition. Although computational tools have been developed to analyze grammatical complexity, most relevant studies investigated this construct in the context of English as a second language. In response to an increasing number of L2 Chinese learners, it is important to extend the investigation of grammatical complexity in L2 Chinese. To promote relevant research, we evaluated the new computational tool, Stanza, on its accuracy of part-of-speech tagging for L2 Chinese writing. We particularly focused on eight grammatical features closely related to L2 Chinese development. Then, we reported the precisions, recalls, and F-scores for the individual grammatical features and offered a qualitative analysis of systematic tagging errors. In terms of the precision, three features have high rates, over 90% (i.e., ba and bei markers, classifiers, -de as noun modifier marker). For recall, four features have high rates, over 90% (i.e., aspect markers, ba and bei markers, classifiers, -de as noun modifier marker). Overall, based on the F-scores, Stanza has a good tagging performance on ba and bei markers, classifiers, and -de as a noun modifier marker. This evaluation provides research implications for scholars who plan to use this computational tool to study L2 Chinese development in second language acquisition or applied linguistics in general.
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