Named Entity Recognition with Bidirectional LSTM-CNNs
Table 10: Per genre F1 scores on OntoNotes. BC = broadcast conversation, BN = broadcast news, MZ = magazine, NW = newswire, TC = telephone conversation, WB = blogs and newsgroups
['[BOLD] Model', '[BOLD] BC', '[BOLD] BN', '[BOLD] MZ', '[BOLD] NW', '[BOLD] TC', '[BOLD] WB']
As expected, our model performs best on clean text like broadcast news (BN) and newswire (NW), and worst on noisy text like telephone conversation (TC) and Web text (WB). Our model also substantially improves over previous work on all genres except TC, where the small size of the training data likely hinders learning.