A Discriminative Neural Model for Cross-Lingual Word Alignment
Table 3: Precision, Recall, and F1 on Arabic GALE test data.
['Method', 'P', 'R', 'F1']
Furthermore, we see that average attention performs abysmally in Arabic. The best thresholds for Arabic differed substantially from those for Chinese: for average attention (with and without BPE) the values were α=0.05 and α=0.1, while for the discriminative aligner they were α=0.94 and α=0.99 (compared to 0.15 for Chinese). This is reflected in the high precision of the discriminative aligner.