Structural probes train on Universal Dependencies (UD), which does not encode formal-syntactic abstractions such as phase boundaries or phase-internal cohesion. Whether large language models (LLMs) encode these remains an open question that UD-based probing cannot answer by construction. We evaluate structural probes on wh-movement stimuli where UD distances are invariant across conditions by design -- any non-zero effect therefore reflects structure beyond UD. The three conditions -- bare small clause, infinitival, and finite -- are ordered by the number of Minimalist Program (MP) phase boundaries the wh-element crosses. Across 13 LLMs from four families, we find a phase-count gradient on a cross-clause pair (12/13 models) and a 13/13 sign asymmetry on a within-clause pair whose UD distance is identical across conditions -- the latter specifically predicted by phase-internal cohesion, an MP abstraction invisible to UD by construction. Activation patching confirms the representations are causally active in 12/13 models. These findings suggest that distributional pretraining can induce representations aligned with formal-syntactic abstractions beyond the reach of annotation-based probing; UD-grounded probes provide a lower bound on syntactic encoding, not an upper bound.

翻译：结构探针基于普遍依存关系（UD）进行训练，而UD本身并不编码形式句法抽象概念，如语段边界或语段内部凝聚力。大型语言模型（LLMs）是否编码了这些概念仍是一个开放问题，基于UD的探针因设计局限无法回答。我们针对wh-移位刺激评估结构探针——在这些刺激中，不同条件下的UD距离被设计为不变：因此任何非零效应都反映了超越UD的结构。三个条件——裸小句、不定式从句和定式从句——依据wh-成分跨越的最小方案（MP）语段边界数量排序。在来自四个家族的13个LLM中，我们发现跨从句配对存在语段计数梯度（12/13模型），而从句内配对在UD距离跨条件完全一致时仍呈现13/13的符号不对称——后者恰好由语段内部凝聚力（一种UD架构上不可见的MP抽象概念）预测。激活修补证实这些表征在12/13模型中具有因果作用。这些发现表明，分布式预训练可以诱发与形式句法抽象概念对齐的表征，这些抽象概念超越了基于标注的探测范围；基于UD的探针提供的是句法编码的下界，而非上界。