Dependency-Guided LSTM-CRF for Named Entity Recognition
Table 7: Low-resource NER performance on the SemEval-2010 Task 1 datasets.
['[BOLD] Model', '[BOLD] Catalan  [BOLD] Prec.', '[BOLD] Catalan  [BOLD] Rec.', '[BOLD] Catalan  [BOLD] F [BOLD] 1', '[BOLD] Spanish  [BOLD] Prec.', '[BOLD] Spanish  [BOLD] Rec.', '[BOLD] Spanish  [BOLD] F [BOLD] 1']
We assume that the contextualized word representations are not available and dependencies are predicted. With limited amount of training data, BiLSTM-CRF suffers from low recall and the DGLSTM-CRF largely improves it on these two datasets. Using gold dependencies further significantly improves the precision and recall.