The time-course of prediction in incremental sentence processing: Evidence from anticipatory eye movements
The time-course of prediction in incremental sentence processing: Evidence from anticipatory eye movements
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DOI：
10.1016/s0749-596x(03)00023-8
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发表时间：
2003-07-01
影响因子：
4.3
通讯作者：
Haywood, SL
中科院分区：
文献类型：
--
作者：
Kamide, Y;Altmann, GTM;Haywood, SL
描述了使用“视觉世界”范式的三个眼球追踪实验，这些实验探索了在明确表示这些依赖性的语言输入之前评估主题依赖性的基础。 Altmann 和 Kamide (1999) 发现动词传达的选择信息可以用来预测即将到来的主题，我们试图在这里更准确地描绘出这种预期处理的基础。我们来自两项英语研究和一项日语研究的数据表明，（a）基于动词的信息不仅限于预测紧随其后的（语法）宾语，还可以预测后来发生的宾语（例如，目标），（b）与动词传达的信息相结合，动词前的论元（主体）可以限制对后续主题的预期，以及（c）在头尾结构中，例如日语中常见的句法和语义 从前语言论证中提取的约束实际上可以在没有中心词（动词）的情况下对即将到来的进一步论证进行预期。我们认为，这种处理是增量处理器的标志，它能够尽早利用不同的信息源（一些非语言信息），以便对每个时刻的输入建立尽可能完整的解释。 (C) 2003 年爱思唯尔科学（美国）。版权所有。
Three eye-tracking experiments using the 'visual-world' paradigm are described that explore the basis by which thematic dependencies can be evaluated in advance of linguistic input that unambiguously signals those dependencies. Following Altmann and Kamide (1999), who found that selectional information conveyed by a verb can be used to anticipate an upcoming Theme, we attempt to draw here a more precise picture of the basis for such anticipatory processing. Our data from two studies in English and one in Japanese suggest that (a) verb-based information is not limited to anticipating the immediately following (grammatical) object, but can also anticipate later occurring objects (e.g., Goals), (b) in combination with information conveyed by the verb, a pre-verbal argument (Agent) can constrain the anticipation of a subsequent Theme, and (c) in a head-final construction such as that typically found in Japanese, both syntactic and semantic constraints extracted from pre-verbal arguments can enable the anticipation, in effect, of a further forthcoming argument in the absence of their head (the verb). We suggest that such processing is the hallmark of an incremental processor that is able to draw on different sources of information (some non-linguistic) at the earliest possible opportunity to establish the fullest possible interpretation of the input at each moment in time. (C) 2003 Elsevier Science (USA). All rights reserved.