A new neuro-symbolic pipeline utilizing 2.5-D decomposition significantly improves the spatial reasoning of large language models (LLMs) in autonomous construction tasks, achieving 94.6% accuracy on the Build What I Mean benchmark. This advancement suggests broader applications in autonomous systems where physical constraints are present, enhancing reliability in structural assembly.