Set Prediction for Aspect Sentiment Triplet Extraction
In recent years,aspect-based sentiment analysis(ABSA)has received more and more attention.Among them,aspect sentiment triplet extraction(ASTE)is the key subtask that requires extracting the aspect words and opinion words of the sentence at the same time and outputting the corresponding sentiment polarity.Most previous work has used the pipeline approach for extraction,ignoring the connection between aspect words and opinion words.This paper proposes to treat the aspect sentiment triplet extraction problem as a set prediction issue,and performs triplet extraction in an end-to-end manner.Experiments on multiple benchmark datasets show that the model proposed in this paper has achieved better results.