Neural Models for Sequence Chunking
Table 1: Text chunking results of our neural sequence chunking models.
['[EMPTY]', 'F1', 'Segment-F1']
“F1” is the final evaluation metric, and “segment-F1” refers to the segmentation F1-score. From the table, we can see that Model I and Model II only have comparable results with the baseline on both evaluation metrics - segment-F1 and final F1 score. Hence, we infer that using IOB labels to do segmentation independently might not be a good choice. However, Model III outperforms the baseline on both segmentation and labeling.