Who Blames Whom in a Crisis? Detecting Blame Ties from News Articles Using Neural Networks
Table 6: Experiment results of Context Model using different pooling functions.
['[BOLD] Model BoERand', '[BOLD] dev F1 54.60', '[BOLD] Model', '[BOLD] dev F1']
As stated in the Context Model section, we compare different pooling methods used to aggregate multiple contexts representations, and bi-directional LSTM with a single forward LSTM. BiLSTM works better than LSTM for every pooling method since we can take advantage of information from both directions of the sentence. Random pooling has the worst result, mainly because a lot of important information is lost. Max pooling has the highest score on most cases, therefore we use BiLSTM + max pooling in the following experiments.