Open-Domain Targeted Sentiment Analysis via Span-Based Extraction and Classification
2019, ACL data: SemEval 2014, SemEval 2014 ABSA, SemEval 2015, SemEval 2016 task: ABSA propose a span-based extract-then-classify framework, where multiple opinion targets are directly extracted from the sentence under the supervision of target span boundaries, and corresponding polarities are then classified using their span representations. 优点： 用指针网络选取target，避免了序列标注的搜索空间过大问题 用span边界+极性的标注方式，解决多极性的target问题 方法 Input: sentence x =(x1,..., xn) with length n, Target list T = {t1,..., tm}： each target ti is annotated with its start, end position, and its sentiment polarity...