PAI at SemEval-2022 Task 11: Name Entity Recognition with Contextualized Entity Representations and Robust Loss Functions
Long Ma, Xiaorong Jian, Xuan Li · Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022) · 2022
This paper describes our system used in the SemEval-2022 Task 11 Multilingual Complex Named Entity Recognition, achieving 3rd for track 1 on the leaderboard.We propose Dictionary-fused BERT, a flexible approach for entity dictionaries integration.The main ideas of our systems are: 1) integrating external knowledge (an entity dictionary) into pretrained models to obtain contextualized word and entity representations 2) designing a robust loss function leveraging a logit matrix 3) adding an auxiliary task, which is an on-top binary classification to decide whether the token is a mention word or not, makes the main task easier to learn.It is worth noting that our system achieves an F1 of 0.914 in the postevaluation stage by updating the entity dictionary to the one of Meng et al. (2021), which is higher than the score of 1st on the leaderboard of the evaluation stage.