SentiBERT: A Transferable Transformer-Based Architecture for Compositional Sentiment Semantics
Table 4: Evaluation for contrastive relation (%). We show the accuracy for triple-lets (‘X but Y’, ‘X’, ‘Y’). X and Y must be phrases in our experiments.
['[BOLD] Models', '[BOLD] Accuracy']
: We evaluate the effectiveness of SentiBERT with regards to tackling contrastive relation problem. Here, we focus on the contrastive conjunction “but”. We pick up the sentences containing word ‘but’ of which the sentiments of left and right parts are different. In our analysis, a ‘X but Y’ can be counted as correct if and only if the sentiments of all the phrases in triple-let (‘X but Y’, ‘X’ and ‘Y’) are predicted correctly. SentiBERT outperforms other variants of BERT about 1%, demonstrating its ability in capturing contrastive relation in sentences.