Aspect Sentiment Triplet Extraction (ASTE) is an emerging task to extract a given sentence's
triplets, which consist of aspects, opinions, and sentiments. Recent studies tend to address …

Abstract Aspect Sentiment Triplet Extraction (ASTE) is a subtask of Aspect-based Sentiment
Analysis (ABSA). Recently, ASTE methods have achieved promising results. However, the …

Aspect Sentiment Triple Extraction (ASTE) is an emerging task in fine-grained sentiment
analysis. Recent studies have employed Graph Neural Networks (GNN) to model the syntax …

Most existing aspect sentiment triplet extraction models emphasize the adoption of novel
tagging scheme to jointly extract three elements of sentiment triplets, but they overlook the …

Aspect sentiment triplet extraction (ASTE), which focuses on mining the triplets (aspect,
opinion, sentiment), is a complex and integrated subtask in aspect-based sentiment …

Abstract Within fine-grained Aspect-Based Sentiment Analysis, one of the critical subtasks is
Aspect Sentiment Triplet Extraction, which aims to extract all triplets from user comments …

In this work we investigate the capability of Graph Attention Network for extracting aspect
and opinion terms. Aspect and opinion term extraction is posed as a token-level …

Aspect-Sentiment Triplet Extraction (ASTE) is a recently proposed task of aspect-based
sentiment analysis that consists in extracting (aspect phrase, opinion phrase, sentiment …

In this paper, we extend financial sentiment analysis~(FSA) to event-level since events
usually serve as the subject of the sentiment in financial text. Though extracting events from …

With the increasing frequency of documents appearing in scenarios including online
comments, car reviews and movie evaluations, the text length in sentiment analysis tasks …