Translating natural language requirements into Signal Temporal Logic (STL) is essential for safety-critical systems but requires mathematical expertise. We propose a translational grammar mapping Universal Dependencies (UD) structures to STL Operators through 17 theoretically-motivated patterns, evaluated on the NL2TL benchmarking dataset of 7,002 expert-annotated sentence-STL pairs, and an additional cross-domain analysis. We built a parser guided by this grammar to explore the formal deterministic relationship between UDR Compositions and STL Operators, achieving ~99% sentence coverage, ~54% exact matches (and ~97% similarity). Sentence-level regression analyses predict STL statements and STL Operator classes, considering the co-occurance of UDR substructures (UDR components) with an accuracy of more than ~74% and ~81%, respectively. They uncover a new logical grammatical link between temporal NL and formal logic, that is conditioned by the sentence-level context, and provide insights into how linguistic theory unfolds in practice through temporal linguistic expressions.