Semi-Supervised Neural System for Tagging, Parsing and Lemmatization
Table 3: Comparison of the standard (std) and self-training (self) models on the validation set using the gold-standard segmentation. Note that ‘kk_ktb’ (Kazakh) and ‘ga_idt’ (modern Irish) treebanks do not have validation sets, so we are unable to report any results.
['[BOLD] Treebank', '[BOLD] LAS  [BOLD] std', '[BOLD] LAS  [BOLD] self', '[BOLD] MLAS  [BOLD] std', '[BOLD] MLAS  [BOLD] self', '[BOLD] BLEX  [BOLD] std', '[BOLD] BLEX  [BOLD] self']
There is an increase for all metrics for all treebanks except for ‘zh_gsd’ (Chinese). On average there is an increase of 1.2 p.p. for LAS, 2.9 p.p. for MLAS and 1.7 p.p. for BLEX.