Delimiting native and foreign syntax in Early Slavonic by enhancing digital corpora: non-finite clauses as intermediate phenomena

我的研究项目的总体目标是通过增强数字语料库和采用定量方法，为关于旧教会斯拉夫语（OCS）中本地和借用句法元素的划界的长期辩论做出贡献，OCS是现存最古老的斯拉夫语手稿的语言。这场争论源于这样一个事实，即几乎所有现存的文本在OCS是从新约希腊语翻译。这通常使得区分奴隶希腊语calques和真正的斯拉夫语结构变得很有挑战性，特别是考虑到这两种语言具有总体上相对相似的语言结构。我的项目将试图评估语言外部和语言内部因素的相对重要性，在确定分布的非限定子句在OCS：这些结构可以被看作是一个中间组的现象之间的本地和外国的两端的一个假设的“光谱的原生性”，因为它们通常被认为是基本上本地的结构，扩大了其范围下希腊的影响。为了定量地证实这一想法，并更好地了解激发不同类型现象分布的复杂因素，我将使用不同的统计模型和两个不同的数据集。分类树是一个成功的模型，可以预测各种因素，这些因素决定了希腊-斯拉夫语谱中更极端现象的行为，例如组成顺序（最大程度地模仿希腊语）和所有格结构（实际上完全独立于希腊语）。应用这样一个模型来评估非限定从句，预计会产生非常不同的结果：希腊语和语言内部的预测应该排名相对较高的预测。希腊语因素的相对排名可能表明每个结构的不同“本土化水平”，而语言内部因素的相对重要性可能反过来又会激发它们在斯拉夫语中句法-语义界面的地位。在我的项目中，一个关键的步骤是将希腊-斯拉夫语平行分析的结果与后来原始文本中相同现象的分布进行比较（即在后期教会斯拉夫语和白话文学）。为了做到这一点，TOROT（选定的语料库）将通过添加大量原始早期斯拉夫语文本来增强（主要是南斯拉夫语），然后将自动预处理（词形化和标记词性和词法），并针对相关句法现象进行策略性注释。

The overarching goal of my research project is to contribute to the long-standing debate on the delimitation of native and borrowed syntactic elements in Old Church Slavonic (OCS), the language of the oldest extant Slavonic manuscripts, by enhancing digital corpora and employing quantitative methods. The debate stems from the fact that virtually all of the extant texts in OCS are translations from New Testament Greek. This often makes it challenging to distinguish slavish Greek calques from genuinely Slavonic constructions, especially considering that the two languages have overall comparatively similar linguistic structures. My project would attempt to assess the relative importance of language-external and language-internal factors in determining the distribution of non-finite clauses in OCS: these constructions could be seen as an intermediate group of phenomena between the native and the foreign ends of a hypothetical 'spectrum of nativeness', as they are generally thought to be essentially native constructions which have expanded their scope under Greek influence. In order to substantiate this thought quantitatively and have a better picture of the complex set of factors motivating the distribution of the different types of phenomena, I would be using different statistical models and two different datasets. Classification trees have been a successful model in predicting the various factors determining the behaviour of more extreme phenomena in the Greek-Slavonic spectrum, such as constituent order (imitating Greek to the greatest extent) and possessive constructions (practically completely independent of Greek). The application of such a model to the assessment of non-finite clauses is expected to produce very different results: both the Greek and the language-internal predictors should rank relatively high as predictors. The relative ranking of the Greek factors might indicate different 'levels of nativeness' of each constructions, whereas the relative importance of the language-internal factors might in turn motivate their status within Slavonic at the syntax-semantic interface. A crucial step in my project would be comparing the results yielded in the Greek-Slavonic parallel analyses with the distribution of the same phenomena in later original texts (i.e. in Later Church Slavonic and vernacular literature).In order to do so, TOROT (the chosen corpus) would be enhanced by adding a considerable amount of original Early Slavonic texts (mostly South Slavonic), which would then be automatically pre-processed (lemmatised and tagged for part of speech and morphology) and strategically annotated for the relevant syntactic phenomena.