Fine-Grained Argument Unit Recognition and Classification

Understand

Prior work has commonly defined argument retrieval from heterogeneous document collections as a sentence-level classification task.

• Consequently, argument retrieval suffers both from low recall and from sentence segmentation errors making it difficult for humans and machines to consume the arguments.
• In this work, we argue that the task should be performed on a more fine-grained level of sequence labeling.
• For this, we define the task as Argument Unit Recognition and Classification (AURC).