Cross-Sentence N-ary Relation Extraction with Graph LSTMs
Table 2: Average test accuracy in five-fold cross-validation for drug-mutation binary relations, with an extra baseline using a BiLSTM on the shortest dependency path [Xu et al.2015b, Miwa and Bansal2016].
['[BOLD] Model', '[BOLD] Single-Sent.', '[BOLD] Cross-Sent.']
We conducted the same experiments on the binary sub-relation between drug-mutation pairs. BiLSTMs on the shortest path substantially underperformed BiLSTMs or graph LSTMs, losing between 4-5 absolute points in accuracy, which could be attributed to the lower parsing quality in the biomedical domain. We attributed the gain to the fact that \newcitemiwa2016end used separate LSTMs for the linear chain and the dependency tree, whereas graph LSTMs learned a single representation for both.