A panoramic view of acceptability judgments in Polish generative linguistics

IF 0.5 4区 文学 0 LANGUAGE & LINGUISTICS Poznan Studies in Contemporary Linguistics Pub Date : 2023-11-27 DOI:10.1515/psicl-2022-1067
Paulina Łęska-Bayraktar, Sylwiusz Żychliński
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Abstract

This article aims to provide a concise overview of the most relevant topics concerning the implementation of acceptability judgments in generative research. The first part focuses on theoretical issues, including the reasons underlying the prevalence of acceptability judgments, the skepticism towards the wide use of informal judgments, the arguments for and against the continued use of informal data points and the challenges related to experimental data collection and the gradient nature of judgments. The second part further explores the concept of gradient acceptability and its different sources. We suggest that violations of soft constraints correspond with partial acceptability, unlike violations of hard constraints, which cause strong unacceptability. Based on our investigation of selected partially acceptable syntactic phenomena in Polish, we show that their syntactic accounts can also benefit from the inclusion of non-syntactic factors, which can be more reliably identified via experimental methodology. More specifically, we propose that (i) the lack of subject orientation of pronominal possessives could be attributed to lexical ambiguity, (ii) coreference of possessive cataphora is facilitated by antecedent backgrounding and (iii) WCO is improved by focus marking of the possessive pronoun, (iv) while processing of the last two structures could be ameliorated with more informative fillers.
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波兰语生成语言学中可接受性判断的全貌
这篇文章的目的是提供一个关于可接受性判断在生成研究中实施的最相关主题的简要概述。第一部分侧重于理论问题,包括可接受性判断普遍存在的原因,对广泛使用非正式判断的怀疑,支持和反对继续使用非正式数据点的论点,以及与实验数据收集和判断的梯度性质相关的挑战。第二部分进一步探讨了梯度可接受性的概念及其不同来源。我们认为违反软约束与部分可接受性相对应,而违反硬约束则导致强烈的不可接受性。根据我们对波兰语中部分可接受的句法现象的调查,我们表明他们的句法解释也可以从包含非句法因素中受益,这些因素可以通过实验方法更可靠地识别出来。更具体地说,我们认为(1)代词所有格缺乏主语指向可能归因于词汇歧义;(2)先行词背景促进了所有格指示语的共指;(3)所有格代词的焦点标记改善了WCO;(4)后两种结构的处理可以通过更多的信息填充来改善。
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