Natural Language Processing for Achieving Sustainable Development:the Case of Neural Labelling to Enhance Community Profiling
Table 3: Single label performance and support in the S2I corpus. Results obtained with the best model (T1+T2+T3 training), rounding predictions at 0.5 and evaluating with the real_simulation setting.
['T1', 'T3', 'P', 'R', '[ITALIC] F1', 'Supp', '%']
Error Analysis. We perform a detailed error analysis of the best performing model’s predictions in the real_simulation setting, which proved to be more challenging. Not surprisingly, particularly good performance is often obtained on T3 labels which often correlate with specific terms (as School Fees, or Faith). The analysis of the ROC curves shows that, overall, satisfactory results are obtained for all T1 labels considered (Appendix D), leaving, however, considerable room for future research.