id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_6n2v2a3dwvgbndggzshipvmfpy	Sebastian Martschat	Latent Structures for Coreference Resolution	2015	14	.pdf	application/pdf	8781	919	65	of different approaches to coreference resolution in terms of the structure they operate In particular, we analyze approaches to coreference resolution and point out that they mainly differ in the structures they operate on. we develop a machine learning framework for structured prediction with latent variables for coreference differ in the scope (pairwise, per anaphor, per document, ...) they employ while learning a scoring function for these pairs, and the way the consolidating is focus on accounting for the latent structures underlying coreference resolution approaches. In our framework, we can represent the mention pair model as a labeled graph. The cost function from the mention ranking model naturally extends to the tree case When viewing coreference resolution as prediction of latent structures, entity-based models operate on structures that relate sets of mentions to While antecedent trees give results with the highest precision, a mention ranking model with latent	./cache/work_6n2v2a3dwvgbndggzshipvmfpy.pdf	./txt/work_6n2v2a3dwvgbndggzshipvmfpy.txt