QA4IE: A Question Answering based Frameworkfor Information Extraction
Table 5: Model ablation on QA4IE-SEQ-S. The first line is our original model and each of the following lines is the original model with a component ablated.
['[EMPTY]', 'EM / F1', 'Training hours']
We do not involve Attention Flow Layer and Pointer Network Decoder as they cannot be replaced by other architectures with the model still working. We can observe that the first three components can effectively improve the performance but Self Matching Layer makes the training more computationally expensive by 40%. Besides, the LSTMBlockFusedCell works effectively and accelerates the training process by 6 times without influencing the performance.