The key insight is to label each word with a set of target tags (e.g., B, I, O) as well as a set of polarity tags (e.g., +, -, 0), or use a more collapsed set of tags (e.g., B+, I-) to directly indicate the boundary of targeted sentiment, as shown in Figure 2(a).
the entire task is formulated as a sequence tagging problem, and solved using either a pipeline model, a joint model, or a collapsed model under the same network architecture.