Turkish PoS Tagging by Reducing Sparsity with Morpheme Tags in Small Datasets
Table 2: Morpheme tagging F1 scores for different training set sizes on Metu-Sabancı Turkish Treebank
['Train set size', 'Test set size', 'Number of tags', 'F1 Score']
We used Zemberek again in order to create gold sets for the morpheme tagging task. The F1 score of the model is 80.7% for a training set with 500 words, whereas the F1 score increases up to 94.1% on a 5K training set. Therefore, the F1 score significantly improves on the larger training sets.