本研究在英国国家语料库(BNC)的口语子库内,穷尽调查了语用助词actually在句内前后位置、说话人性别、商务与日常语域、对话与自述语段上的语用功能分布变化。研究利用循环神经网络工具,通过描写搭配类型的变化程度,对语用属性开展分类预测,以此揭示语用功能的搭配变化率在不同语用属性上的收敛情况。研究发现,语用功能的搭配变化受句法与语域的支配效应要高于性别与交互程度。这扩充了“主体性-主体间性边界假设”,修正了“交互突变效用假设”。研究简化了语用功能的分析方法,为语料库应用研究推进信息技术与数字人文的融合创新,探索语用型式模拟的操作方案。

This study exhaustively examines “actually” in the spoken data from the BNC in terms of its collocation variability across syntax, gender, domain and interactivity, based on which pragmatic functions are classified by applying the Recurrent Neural Network (RNN) model. It reveals which pragmatic classifier controls the collocation variability of pragmatic functions. It is found that the significance of syntax and domain controls is higher than that of gender and interactivity. The specific patterns of convergence between pragmatic classifiers and collocation variants revise the Subjectivity Intersubjectivity Peripheries Hypothesis and marginalizes the efficacy of interactional exigency. These enlighten a corpus-based solution to parameterizing the functionality of pragmatic inferences from units of meaning under the canopy of data-driven research to combine digital humanities with information technologies.