Skip to Main Content
Table 5 
Accuracy of our system, Contextualized Translation (CT), using the data set PhrasalVerbsToSpanish, together with the scores obtained with state-of-the-art machine translators: DeepL, Google Translator, Bing, and Yandex (all consulted in December 2017). Four baseline methods, based on looking up our bilingual lexicon of phrasal verbs, are also evaluated along with an unsupervised machine translation system, UNdreaMT (Artetxe et al. 2017). The last column shows the statistical significance test comparing each system with the previous one in the table.
systemspositivenegativeaccuracys-test
Dict-first 349 770 0.312   
Dict-Corpus-Based 375 744 0.335 
Dict-Nocomp 430 689 0.383 ≫ 
Dict-Nocomp-VecMap 437 682 0.390 ∼ 
  
CT 571 548 0.510 ≫ 
  
DeepL 501 618 0.447 ≪ 
Google Trans. 410 709 0.366 ≪ 
Bing 326 793 0.291 ≪ 
Yandex 281 838 0.251 
  
UNdreaMT 12 1,107 0.010 ≪ 
systemspositivenegativeaccuracys-test
Dict-first 349 770 0.312   
Dict-Corpus-Based 375 744 0.335 
Dict-Nocomp 430 689 0.383 ≫ 
Dict-Nocomp-VecMap 437 682 0.390 ∼ 
  
CT 571 548 0.510 ≫ 
  
DeepL 501 618 0.447 ≪ 
Google Trans. 410 709 0.366 ≪ 
Bing 326 793 0.291 ≪ 
Yandex 281 838 0.251 
  
UNdreaMT 12 1,107 0.010 ≪ 
Close Modal

or Create an Account

Close Modal
Close Modal