Fine-grained Knowledge Fusion for Sequence Labeling Domain Adaptation
Table 5: Results of the strongly/weakly relevant elements on the Twitter test set.
['Methods', 'POS Strong', 'POS Weak', 'NER Strong', 'NER Weak']
To further probe into the experimental results of the fine-grained knowledge fusion, we classify the target test data (in element level) into two classes: strongly relevant and weakly relevant, based on their relevance degrees to the source domain. The partition threshold is according to the average relevance score of the target training data.