EAGER: Joint Learning for Knowledge-Rich Coreference Resolution

这项探索性研究的早期资助旨在调查知识丰富，联合学习方法的可行性，以推进共同参考解决方案的最终目标。鉴于词汇语义和语篇研究的最新进展，以及大规模词汇数据库的发展，本基金的第一个目标是调查现有的语言技术是否足够成熟，能够从结构化和非结构化数据中准确地提取语义、语篇和世界知识，以便在使用这些知识时显著改进基于学习的共参考系统。第一个目标的基础假设是使用管道系统架构，其中来自各种来源的复杂语言信息在共同参考解析之前被计算。虽然在共参考研究中普遍采用管道架构，但上游组件产生的误差可能会传播到共参考组件，从而对其性能产生不利影响。为了解决这个问题，本基金的第二个目标是探索一种方法，在这种方法中，以联合的方式学习管道中的多个任务。虽然大多数关于语言处理联合学习的研究都集中在两个任务上，但本研究试图通过同时学习语义、话语和信息提取方面的大量任务，将联合学习中的挑战提升到一个新的水平，这些任务都可以从学习过程中的相互作用和相互参照中受益。

This Early Grant for Exploratory Research seeks to investigate the viability of a knowledge-rich, joint-learning approach to coreference resolution, with the ultimate goal of advancing the state of the art in coreference resolution. Given recent advances in research on lexical semantics and discourse, and the development of large-scale lexical databases, the first objective of this grant is to investigate whether existing language technologies are mature enough to accurately extract semantic, discourse, and world knowledge from structured and unstructured data so that learning-based coreference systems can be significantly improved when such knowledge is employed.An assumption underlying the first objective is the use of a pipeline system architecture, where sophisticated linguistic information from various sources is computed prior to coreference resolution. While a pipeline architecture is popularly-used in coreference research, the errors made by the upstream components may propagate to the coreference component and adversely affect its performance. To address this problem, the second objective of this grant is to explore an approach in which multiple tasks in the pipeline are learned in a joint fashion. While most research on joint learning for language processing focuses on two tasks, this work seeks to take the challenge involved in joint learning to the next level by simultaneously learning a large number of tasks in semantics, discourse, and information extraction, which can all benefit from their interactions with each other and with coreference in the learning process.