The ordered statistic decoding (OSD) algorithm for short-length linear block codes provides an attractive ML-approaching performance, expected to be used for the ultra-reliable low latency communication (URLLC) at the next-generation wireless solutions. To find the corrected code-word among numerous candidates, however, the decoding process requires a considerable amount of computational costs, which need to be simplified to achieve low-latency processing. In this letter, we present several schemes that relax the overall complexity of the state-of-the-art segmentation discarding algorithm. Without degrading the error-correcting power, our method approximate the internal steps for computing the segment sizes and the stopping bounds at the run time, reducing the average processing costs by 1.6 x 10(4) times for achieving the low-BLER performance.