Abstract In this study, we aim to demonstrate the effectiveness of network science in exploring the emergence of constructional semantics from the connectedness and relationships between linguistic units. With Mandarin locative constructions (MLCs) as a case study, we extracted constructional tokens from a representative corpus, including their respective space particles (SPs) and the head nouns of the landmarks (LMs), which constitute the nodes of the network. We computed edges based on the lexical similarities of word embeddings learned from large text corpora and the SP-LM contingency from collostructional analysis. We address three issues: (1) For each LM, how prototypical is it of the meaning of the SP? (2) For each SP, how semantically cohesive are its LM exemplars? (3) What are the emerging semantic fields from the constructional network of MLCs? We address these questions by examining the quantitative properties of the network at three levels: microscopic (i.e., node centrality and local clustering coefficient), mesoscopic (i.e., community) and macroscopic properties (i.e., small-worldness and scale-free). Our network analyses bring to the foreground the importance of repeated language experiences in the shaping and entrenchment of linguistic knowledge.

中文翻译：

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词、构式和语料库：普通话空间粒子构式语义的网络表示

摘要 在这项研究中，我们旨在证明网络科学在从语言单元之间的连通性和关系中探索构造语义的出现方面的有效性。以普通话位置结构（MLC）为案例研究，我们从代表性语料库中提取了结构标记，包括它们各自的空间粒子（SP）和地标（LM）的头部名词，它们构成了网络的节点。我们基于从大型文本语料库中学习到的词嵌入的词汇相似性和来自搭配分析的 SP-LM 偶然性来计算边缘。我们解决三个问题：（1）对于每个 LM，SP 的含义有多典型？(2) 对于每个 SP，它的 LM 示例在语义上的凝聚力如何？（3）MLCs的构造网络中新兴的语义场是什么？我们通过在三个层面检查网络的定量属性来解决这些问题：微观（即节点中心性和局部聚类系数）、中观（即社区）和宏观属性（即小世界和无标度）。我们的网络分析突出了重复语言经验在语言知识的塑造和巩固中的重要性。