A More Fine-Grained Aspect–Sentiment–Opinion Triplet Extraction Task

Sentiment analysis aims to systematically study affective states and subjective information in digital text through computational methods. Aspect Triplet Extraction (ASTE), a subtask of sentiment analysis, extract aspect term, opinion term triplets from sentences. However, some ASTE’s extracted are not self-contained, as they reflect the sentence’s toward between terms. These only unhelpful people, but can also be detrimental downstream tasks. In this paper, we introduce more nuanced task, Aspect–Sentiment–Opinion (ASOTE), which extracts triplets. triplet with ASOTE is pair. We build four datasets for ASOTE. A Position-aware BERT-based Framework (PBF) proposed address PBF first terms For each generates an term-specific sentence representation, considering term’s position. It then associated predicts sentiments aspect–opinion pairs based on representation. experiments datasets, has set benchmark performance novel task.