Quantitative Mapping of Conceptual Hierarchies and Data-Driven Taxonomies of Japanese Architectural Concepts: A 28-Term Testbed

Discourse on Japanese architecture relies on qualitative interpretation to link abstract concepts such as “ma” and “mu”, used here as illustrative examples of the conceptual register, with physical spaces, such as engawa, yet lacks quantitative, data-driven validation. This study addresses this gap by testing two primary hypotheses: (1) whether abstract Japanese architectural terms form a distinct, computationally recoverable conceptual layer, and (2) whether the corresponding concrete architectural devices cohere into a unified physical mesh rather than being fragmented into unrelated subclusters. We investigate this using a Natural Language Processing (NLP) framework centred on a fine-tuned BERT model, utilising an exhaustive Adjusted Rand Index (ARI) enumeration search over two-way partitions on a target vocabulary of 28 terms. Furthermore, a “definitional audit” compares a FULL corpus against a CLEAN corpus, stripped of explicit glossary-like sentences, to mitigate “shortcut learning”, allowing sensitivity at the conceptual physical boundary to be inspected. Both hypotheses are supported. A stable two-block structure appears across all evaluations, comprising a compact conceptual pocket {aware, ma, mu, wabi, sabi, and wabi_sabi} and a larger physical mesh integrating vocabulary for room, garden, and shrine. Interface structure concentrates in a narrow boundary corridor, most consistently along the engawa–shakkei linkage, with en acting as the principal physical-side interface hub under sparsified network views. In the definitional audit (FULL versus CLEAN), ikezuishi is the only recurrently unstable item, shifting sides under small, defensible changes in corpus cleaning and Japanese-aware sentence segmentation, which is best read as a sensitivity signal rather than a substantive change in macro-structure. Removing glossary-like definitions slightly tightens dispersion while preserving the backbone split, which supports definitional audits as a practical robustness check for distributional studies of architectural vocabularies.