  We propose a combined three pre-trained language models (XLM-R, BART, and
DeBERTa-V3) as an empower of contextualized embedding for named entity
recognition. Our model achieves a 92.9% F1 score on the test set and ranks 5th
on the leaderboard at NL4Opt competition subtask 1.
