We manually investigate the errors made by artificial neural networks for morphological inflection in a target language after pretraining on different source languages. For our qualitative analysis, we make use of the validation set. Therefore, we show validation set accuracies in Table TABREF19 for comparison. We manually annotate the outputs for the first 75 development examples for each source–target language combination. All found errors are categorized as belonging to one of the following categories. 
 Question: How is the performance on the task evaluated?
Comparison of test accuracies of neural network models on an inflection task and qualitative analysis of the errors