id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_hrkwn4taczellcyg24hufs5xk4	Greg Durrett	A Joint Model for Entity Analysis: Coreference, Typing, and Linking	2014	14	.pdf	application/pdf	8656	839	64	In this paper, we describe a joint model of coreference, entity linking, and semantic typing (named entity recognition) using a structured conditional random field. Variables in the model capture decisions about antecedence, semantic type, and entity semantic types and entity links across coreference The ai model coreference antecedents, the ti model semantic types, the ei model entity links, and the qi are latent Wikipedia queries. State-of-the-art approaches to coreference (Durrett and Klein, 2013) and entity linking Our NER model places a distribution over possible semantic types for each mention, which corresponds to a fixed span of the input text. Joint NER and entity linking factors (Section 3.2.1) tie semantic information from Wikipedia articles to semantic type predictions. Joint coreference and entity linking factors (Section 3.2.3) encourage relatedness between evaluate on gold mentions in this setting for comparability with prior work on entity linking; we lift Joint Coreference Resolution and Named-Entity Linking with Multi-Pass	./cache/work_hrkwn4taczellcyg24hufs5xk4.pdf	./txt/work_hrkwn4taczellcyg24hufs5xk4.txt