Effective Use of Transformer Networks for Entity Tracking
Table 3: Performances of different baseline models discussed in Section 3, the ELMo baselines, and the proposed entity-centric approaches with the (D)ocument v (S)entence level variants formulated with both entity (F)irst v. (L)ater. Our ETGPT variants all substantially outperform the baselines.
['[BOLD] Model', '[BOLD] P', '[BOLD] R', '[ITALIC] F1', '[BOLD] Acc', '[BOLD] UR', '[BOLD] CR']
Our best ETGPT model achieves an F1 score of 82.50. Comparing to the baselines (Majority through First) and post-conditioned models, we see that the early entity conditioning is critical to achieve high performance.