Scales or features in verb meaning?: Verb classes as predictors of syntactic behavior
Scales or features in verb meaning?: Verb classes as predictors of syntactic behavior
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动词含义中的尺度或特征？：动词类别作为句法行为的预测因子
DOI：
10.1075/bjl.00007.ver
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发表时间：
2017
影响因子：
--
通讯作者：
Elisabeth
中科院分区：
文献类型：
--
作者：
Verhoeven;Elisabeth
动词中心词的几个句法属性是通过它们的语义属性来解释的。诸如能动性、意志性、静态性等言语特征已被证明是预测其句法行为的多个方面（如被动化、辅助选择等）的有用工具。在当前语言学经验转向的背景下，基于语料库或说话人直觉的研究对离散特征的假设提出了质疑，表明语义特征的诊断涉及梯度。这些发现对语法理论提出了挑战：我们是否有理由假设离散动词类别的存在，或者已建立的属性是否表明了意义的标量维度？基于两项实证研究——可接受性研究和语料库研究——本文探讨了能动性在区分动词类别和预测德语动词句法行为中的作用。可接受性数据表明，主体性的诊断涉及梯度，不能将其简化为随机的变异源。然而，基于这些诊断的代理性标量模型与分类模型的比较表明，书面语料库数据中发现的词序句法变化最好通过假设二元划分为施事动词类和非施事动词类的模型来解释。
Several syntactic properties of verbal heads are accounted for through their semantic properties. Verbal features such as agentivity, volitionality, stativity etc. have been proven a useful tool for predicting several aspects of their syntactic behavior such as passivization, auxiliary selection etc. In the context of the empirical turn in current linguistics, the assumption of discrete features is questioned by studies based on corpora or speakers’ intuitions showing that the diagnostics of semantic features involve gradience. These findings are challenging for grammatical theory: are we justified to assume the existence of discrete verb classes or do the established properties indicate scalar dimensions of meaning? Based on two empirical studies – an acceptability study and a corpus study – the present article examines the role ofagentivityin distinguishing verb classes and in predicting the syntactic behavior of verbs in German. Acceptability data show that the diagnostics of agentivity involve gradience, which cannot be reduced to random sources of variation. However, a comparison of scalar vs. categorical models of agentivity based on these diagnostics reveals that the syntactic variation in word order found in written corpus data is best accounted for through a model that assumes a binary division into a ±agentive and a non-agentive verb class.
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DOI：
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