Turkish PoS Tagging by Reducing Sparsity with Morpheme Tags in Small Datasets
Table 8: Comparison of our model with suffix based tagger [19] and the perceptron algorithm [16] on the datasets obtained from Metu Sabancı Turkish Treebank.
['[EMPTY]', 'Train Set Size', 'Test Set Size', 'Accuracy']
We compared our model with Sak et al. We used the last 5 letters of each word with a second order HMM to implement the suffix based tagger by Dincer et al. The results show that our model outperforms the other two models on smaller datasets (i.e. 5K and 18K).