Does Higher Order LSTM Have Better Accuracy for Segmenting and Labeling Sequence Data?
Table 4: All-Chunking: Comparison with state-of-the-art models.
['[BOLD] All-Chunking', '[BOLD] F1']
We achieve the state-of-the-art performance in all-phrase chunking. \newciteShenSarkar2005 also reported a 95.23 F1-score in their paper. However, this result is based on noun phrase chunking (NP-chunking). All phrase chunking task contains much more tags to predict than NP-chunking, so it is more difficult.