We participate in the DialDoc Shared Task sub-task 1 (Knowledge Identification). The task requires identifying the grounding knowledge in form of a document span for the next dialogue turn. We employ two well-known pre-trained language models (RoBERTa and ELECTRA) to identify candidate document spans and propose a metric-based ensemble method for span selection. Our methods include data augmentation, model pre-training/fine-tuning, post-processing, and ensemble. On the submission page, we rank 2nd based on the average of normalized F1 and EM scores used for the final evaluation. Specifically, we rank 2nd on EM and 3rd on F1.