This paper designs non-adaptive querying policies (NQPs) for the noisy 20 questions game based on error-correction codes. The querying accuracy of a specific NQP is upper bounded by a function of the minimum distance among its codewords. As a result, the row-column constraint is put on codewords of NQPs for scenarios with limited detection to enlarge their minimum distance for improving the querying accuracy, where the limited detection means that only a small number of intervals can be detected at each querying round. Then, it is used to protect the least significant bits in unequal error protection NQPs with linear codes for unlimited detection scenarios. In particular, these structures allow us to deterministically optimize parameters for better querying accuracy. Simulation results show that our methods achieve quantized mean squared error up to several magnitudes compared with the NQPs based on random block coding.