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.
翻译:关系提取和命名实体识别一直被视为需要不同输入数据、标签和模型的两种不同任务。 但是,这两种任务对于结构化情绪分析都至关重要。 我们认为,这两个任务可以合并成一个单一的堆叠模型,有相同的输入数据。 我们进行了不同的实验,以找到最佳模型,从一个句子中提取多种意见图例。 意见图例将由持有者、 目标和表达方式组成。 有了这些意见图例,我们将能够解析我们需要的关系。