SentiLR: Linguistic Knowledge Enhanced Language Representation for Sentiment Analysis
Table 1: Accuracy on sentence-level sentiment classification (SSC) benchmarks (%).
['Model', 'SST', 'MR', 'IMDB', 'Yelp-2', 'Yelp-5']
We can observe that SentiLR-R performs better than all the other baselines on the sentence-level sentiment classification datasets, which indicates that our knowledge-aware representation promotes the understanding of the sentiment in the whole text. We can also see that SentiLR-B / SentiLR-R enhances the performance of vanilla BERT / RoBERTa. This demonstrates that linguistic knowledge and the well-designed pre-training task of SentiLR can adapt to different kinds of BERT-style pre-trained models and improve their performances on the sentence-level sentiment classification benchmarks.