Prior Knowledge Driven Label Embedding for Slot Filling in Natural Language Understanding
TABLE VIII: Performances of the “slot description (BLSTM)” method with varied slot descriptions on FLIGHT. FLIGHT is the target domain, and its 10% training data is used for fine-tuning. “AL(desc.)” denotes the average length of slot descriptions.
['[BOLD] AL(desc.)', '4.0 (ori.)', '7.7', '7.4', '7.0', '6.4', '6.2']
Five participants were asked to describe each slot in the FLIGHT domain. The average length of slot descriptions from different participants varies from 6.2 to 7.7. If we use these slot descriptions in the “slot description (BLSTM)” method when FLIGHT is target domain and 10% training data can be used for fine-tuning, slot F1 scores range from 84.66% to 86.43%.