Perturbed Masking: Parameter-free Probing for Analyzing and Interpreting BERT
Table 5: Experimental results of aspect based sentiment classification.
['[BOLD] Model', '[BOLD] Laptop Acc', '[BOLD] Laptop Macro-F1', '[BOLD] Restaurant Acc', '[BOLD] Restaurant Macro-F1']
We observe that the trees induced from BERT is either on-par (Laptop) or marginally better (Restaurant) in terms of downstream task’s performance when comparing with trees produced by SpaCy. Laptop is considerably more difficult than Restaurant due to the fact that the sentences are generally longer, which makes inducing dependency trees more challenging. We also see that the Eisner trees generally perform better than the right-/left- chain baselines. It is also worth noting that the right-chain baseline also outperforms PWCN+Dep on Restaurant, which leads to an exciting future work that investigates how encoding structural knowledge can help ABSC.