“Translation can’t change a name”: Using Multilingual Data for Named Entity Recognition
Table 5: Category-wise improvement (ΔF1) of NER systems over the baseline model.
['NEs', 'English', 'German', 'Dutch', 'Spanish', 'Avg.']
In order to verify our hypothesis that certain NEs, specially the names of people and locations might not go orthographic changes while transferring to similar languages we look at the category-wise improvement of the NER systems when trained using word clusters of a language (other than self) that gives the best results against the baseline model. For example, for Spanish NER we compare the baseline model with the model trained using French word clusters.