With the wide application of large language models in general-domain text processing

verify ⁃ ing the reliability of entity recognition results has become a critical issue. Targeting at power station oper ⁃ ation and maintenance logs

this paper proposes an entity recognition result verification and original text backtracking method integrating a hybrid matching strategy. This method first leverages prompt engineer ⁃ ing to guide large language models to extract structured entities from unstructured logs

and then designs a three level matching strategy together with similarity based method for reliability verification. Experi ⁃ ments demonstrate that the proposed method can achieve an entity verification accuracy of 82 % on the dataset of power station operation and maintenance logs and can effectively identify entities.