Knowing What, How and Why: A Near Complete Solution for Aspect-based Sentiment Analysis
Table 5: Stage two results in both pair and triplet setting. (+ denotes cascading our stage two module.)
['[EMPTY]', '[EMPTY]', '14res P', '14res R', '14res F', '14lap P', '14lap R', '14lap F', '15res P', '15res R', '15res F', '16res P', '16res R', '16res F']
After obtaining all the possible candidate triplets from the stage one, each triplet is sent to a binary classifier. The classifier was trained on the ground truth aspect and opinion pairs in the training set. The model performing the best on the validation set was used as the stage two classifier for evaluating both our model and baselines. We can observe that our model has achieved steady advantage over other baselines. In addition to evaluating the triplet, we also examine the pure pairing performance for coupling aspects and opinion terms. In both sections, Li-unified-R+, a variant of Li-unified implemented by us, achieved competitive performance on the first three datasets, and even slightly better than ours on 15res in the pairing evaluation.