论文标题
简化跨文档的核心分辨率：评估和建模
Streamlining Cross-Document Coreference Resolution: Evaluation and Modeling
论文作者
论文摘要
跨文档（CD）核心分辨率的最新评估方案通常是不一致或宽大的，从而导致跨工程和高估性能无与伦比的结果。为了促进对此任务的适当研究，我们的主要贡献是提出一种务实的评估方法，该方法仅假设仅访问原始文本，而不是假设黄金提及，无视Singleton的预测，并以CD Coreference解决方案解决了典型的目标设置。旨在为将来的研究设定基线结果，以遵循我们的评估方法，我们为该任务建立了第一个端到端模型。我们的模型适应并扩展了最新的神经模型，以解决文档内部核心分辨率，以解决CD核心设置，从而超出了最先进的结果。
Recent evaluation protocols for Cross-document (CD) coreference resolution have often been inconsistent or lenient, leading to incomparable results across works and overestimation of performance. To facilitate proper future research on this task, our primary contribution is proposing a pragmatic evaluation methodology which assumes access to only raw text -- rather than assuming gold mentions, disregards singleton prediction, and addresses typical targeted settings in CD coreference resolution. Aiming to set baseline results for future research that would follow our evaluation methodology, we build the first end-to-end model for this task. Our model adapts and extends recent neural models for within-document coreference resolution to address the CD coreference setting, which outperforms state-of-the-art results by a significant margin.
