Revealing the Myth of Higher-Order Inference in Coreference Resolution

Understand

This paper analyzes the impact of higher-order inference (HOI) on the task of coreference resolution.

• HOI has been adapted by almost all recent coreference resolution models without taking much investigation on its true effectiveness over representation learning.
• To make a comprehensive analysis, we implement an end-to-end coreference system as well as four HOI approaches, attended antecedent, entity equalization, span clustering, and cluster merging, where the latter two are our original methods.
• We find that given a high-performing encoder such as SpanBERT, the impact of HOI is negative to marginal, providing a new perspective of HOI to this task.