Bianet: A Parallel News Corpus in Turkish, Kurdish and English
Table 4: English-Turkish Experiment Results. Baseline Model News: The model built only using SETIMES corpus. Combined Model News: The model built using SETIMES and the English-Turkish portion of Bianet corpus. Multilingual Model News: The model built using SETIMES and all portions of the Bianet corpus. Best scores are in bold font. All improvements over the baseline are statistically significant (p-value 
['[BOLD] System', '[BOLD] Output Score  [BOLD] BLEU', '[BOLD] Output Score  [BOLD] chrF3']
The model using the extended parallel training corpus achieves a significant improvement of 2.27 BLEU and 0.0204 chrF3 points over the baseline model trained using only previously available SETIMES corpus. The significant improvement of 19.74% on the given evaluation task verifies the quality of human translations in the Bianet corpus and confirms the benefit of its usage for training MT systems in the news domain. Yet, in English-Turkish translation, the best performance is achieved with the multilingual model which incorporates all portions of the Bianet corpus, which outperforms the baseline model by 2.42 BLEU and 0.0221 chrF3 points.