Evaluating the Impact of a Hierarchical Discourse Representation on Entity Coreference Resolution Performance

The contribution of this paper is an empirical investigation of the impact of including a representation Historically, theories of discourse coherence of the hierarchical structure of discourse within (Chafe, 1976; Hobbs, 1979; Grosz and a neural entity coreference approach. To this end, Sidner, 1986; Clark and Brennan, 1991) have offered we leverage a state-of-the-art RST discourse-parser elaborate expositions on how the patterns of to convert a flat document into a tree-like structure anaphoric references in discourse are constrained from which we can derive features that model the by limitations in human capacity to manage structural constraints. We embed this representation attention and resolve ambiguity. Hobbs (1979) within an architecture that is enabled to learn to acknowledges that these human limitations have use this information deferentially depending upon meant that coreference resolution in natural text the type of mention. The results demonstrate that can be achieved with relatively high accuracy using this level of nuance enables a small but significant a combination of recency and simple semantic improvement in coreference accuracy, even with constraints. State-of-the-art neural approaches for automatically constructed RST trees.