AI RESEARCH
Structural-Ambiguity-Aware Translation from Natural Language to Signal Temporal Logic
arXiv CS.CL
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ArXi:2603.28426v1 Announce Type: new Signal Temporal Logic (STL) is widely used to specify timed and safety-critical tasks for cyber-physical systems, but writing STL formulas directly is difficult for non-expert users. Natural language (NL) provides a convenient interface, yet its inherent structural ambiguity makes one-to-one translation into STL unreliable. In this paper, we propose an \textit{ambiguity-preserving} method for translating NL task descriptions into STL candidate formulas.