Object-Verb in Early Modern English: Modelling Markedness

Q2 Arts and Humanities Studia Anglica Posnaniensia Pub Date : 2021-10-01 DOI:10.2478/stap-2021-0016
J. Pérez-Guerra
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Abstract

Abstract Although Verb-Object (VO) is the basic unmarked constituent order of predicates in Present-Day English, in earlier stages of the language Object-Verb (OV) is the preferred pattern in some syntactic contexts. OV predicates are significantly frequent in Old and Middle English, and are still attested up to 1550, when they “appear to dwindle away” (Moerenhout & van der Wurff 2005: 83). This study looks at OV in Early Modern English (EModE), using a corpus-based perspective and statistical modelling to explore a number of textual, syntactic, and semantic/processing variables which may account for what by that time had already become a marked, though not yet archaic, word-order pattern. The data for the study were retrieved from the Penn-Helsinki Parsed Corpus of Early Modern English (1500–1710) and the Parsed Corpus of Early English Correspondence (c.1410–1695), the largest electronic parsed collections of EModE texts. The findings reveal a preference for OV in speech-related text types, which are less constrained by the rules of grammar, in marked syntactic contexts, and in configurations not subject to the general linearisation principles of end-weight and given-new. Where these principles are complied with, the probability of VO increases.
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早期现代英语的宾动关系:模仿标记
虽然动词-宾语(VO)是现代英语中基本的无标记谓语构成顺序,但在语言早期阶段,在某些句法语境中,宾语-动词(OV)是首选模式。OV谓语在古英语和中古英语中非常频繁,直到1550年仍然存在,当时它们“似乎逐渐消失”(Moerenhout & van der Wurff 2005: 83)。本研究着眼于早期现代英语(EModE)中的词序模式,使用基于语料库的视角和统计模型来探索一些文本、句法和语义/处理变量,这些变量可能解释了当时已经成为一种标记的(尽管尚未过时)词序模式。该研究的数据来自宾夕法尼亚-赫尔辛基早期现代英语解析语料库(1500-1710)和早期英语通信解析语料库(c.1410-1695),这是最大的EModE文本电子解析集合。研究结果揭示了语音相关文本类型中对OV的偏好,这些类型受语法规则的约束较少,在标记的句法上下文中,以及在不受末端权重和给定-new的一般线性化原则约束的配置中。在遵守这些原则的地方,VO的可能性增加。
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来源期刊
Studia Anglica Posnaniensia
Studia Anglica Posnaniensia Arts and Humanities-Literature and Literary Theory
CiteScore
0.60
自引率
0.00%
发文量
7
审稿时长
15 weeks
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