Shortcut Sequence Tagging
Table 5: Comparsion of hyper-parameters
['[BOLD] Case', '[BOLD] Variant', '[BOLD] Dev', '[BOLD] Test']
We find that the model does not perform well (94.06%) without using local context windows. Although LSTMs can memorize recent inputs for a long time, it is still necessary to use a convolution-like operator to convolve the input tokens to get a better representation. Character-level information also plays an important role for this task (13% relatively improvement), but the performance would be heavily damaged if using characters only.