A Cluster Ranking Model for Full Anaphora Resolution
Table 6: Comparison between our models and the top performing systems on the conll test set.
['[EMPTY]', 'Models', 'MUC P', 'MUC R', 'MUC F1', 'B3 P', 'B3 R', 'B3 F1', 'CEAF [ITALIC] ϕ4 P', 'CEAF [ITALIC] ϕ4 R', 'CEAF [ITALIC] ϕ4 F1', 'Avg. F1']
Finally, we tested our models on the conll data to assess the performance of our system on the standard data set. We report precision, recall and F1 scores for all three major metrics (MUC, B3 and CEAFϕ4) and mainly focus on the average conll F1 scores presented in the last column. Although the systems by \newcitejoshi2019bert and \newcitejoshi2019spanbert have better results than the \newcitekantor2019bertee system, it is not directly comparable with our system, as their systems are fine-tuned on BERT. Such systems need to be trained on GPUs with 32GB memory, which are not available to our group. By contrast, our system was trained with a GTX 1080Ti GPU with an 11GB memory.