Polyglot Semantic Role Labeling
Table 3: Per-label breakdown of F1 scores for Catalan and Spanish. These numbers reflect labels for each argument; the combination is different from the overall semantic F1, which includes predicate sense disambiguation.
['[EMPTY]', '[BOLD] arg0', '[BOLD] arg1', '[BOLD] arg2', '[BOLD] arg3', '[BOLD] arg4', '[BOLD] arg [ITALIC] L', '[BOLD] arg [ITALIC] M']
Label-wise results. In both languages, we find a small but consistent improvement in the most common label categories (e.g., arg1 and argM). Less common label categories are sensitive to small changes in performance; they have the largest changes in F1 in absolute value, but without a consistent direction. This could be attributed to the addition of English data, which improves learning of representations that are useful for the most common labels, but is essentially a random perturbation for the rarer ones. This pattern is seen across languages, and consistently results in overall gains from polyglot training.