  Relationship extraction and named entity recognition have always been
considered as two distinct tasks that require different input data, labels, and
models. However, both are essential for structured sentiment analysis. We
believe that both tasks can be combined into a single stacked model with the
same input data. We performed different experiments to find the best model to
extract multiple opinion tuples from a single sentence. The opinion tuples will
consist of holders, targets, and expressions. With the opinion tuples, we will
be able to extract the relationship we need.

Computation and Language;Machine Learning