Polyglot Semantic Role Labeling
Table 5: Unlabeled semantic F1 scores on the CoNLL 2009 dataset.
['[BOLD] Model', 'cat', 'ces', 'deu', 'eng', 'jpn', 'spa', 'zho']
S4SS0SSS0Px3 Labeled vs. unlabeled F1. As can be seen here, the unlabeled F1 improvements are generally positive but small, indicating that polyglot training can help both in structure prediction and labeling of arguments. The pattern of seeing the largest improvements on the languages with the smallest datasets generally holds here: the largest F1 gains are in German and Catalan, followed by Japanese, with minimal or no improvement elsewhere.