Year: 2024
Type: article
Abstract: Introduction Previous studies have shown that relative clause (RC) attachment preferences vary across languages, often influenced by factors like morphosyntactic agreement (e.g., number and gender). Mandarin Chinese, with its limited inflectional morphemes compared to Indo-European languages, provides a distinct context for examining this. This study explores relative clause attachment ambiguity in Mandarin by manipulating classifier-noun agreement. Method This study conducted two self-paced reading experiments to investigate the influence of an initial classifier on comprehenders' anticipation of its associated noun and the impact of this prediction on RC attachment preferences in Mandarin Chinese. Results Experiment 1 revealed a significant effect of classifier-noun agreement in offline comprehension: there was an increase in selecting the high-attachment noun (NPhigh) as the RC attachment site when the classifier agreed with NPhigh, whereas there was a decrease in selecting NPhigh when the classifier agreed with the low-attachment noun (NPlow). Online processing results supported this effect, showing that classifiers guide comprehenders' expectations by pre-activating semantic features of the upcoming noun, thus modulating RC attachment preferences. Experiment 2 introduced semantic compatibility between the RC and potential attachment nouns as an additional disambiguating cue, revealing a reliable prediction effect for the upcoming noun. Although the classifier's prediction effect was diminished, it remained influential in this condition. Discussion This study highlights the complexity of relative clause attachment in Mandarin, demonstrating the significant predictive roles of classifier-noun agreement and semantic compatibility.
Source: Frontiers in Language Sciences
Authors: Fengming Liu, Chien-Jer Charles Lin
Institution: Indiana University
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $2,125
Funder: Indiana University Bloomington
OpenAlex ID: W4401826826