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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Efficient One-Pass End-to-End Entity Linking for Questions · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2010.02413/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Mon, 02 Nov 2026 11:16:22 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/2010.02413/feed.xml" rel="self" type="application/rss+xml" /><item><title>Efficient One-Pass End-to-End Entity Linking for Questions — mentioned by deeplstm</title><link>https://news.ycombinator.com/item?id=24903492</link><guid isPermaLink="false">urn:hackerpapers:mention:2010.02413:24903492</guid><pubDate>Tue, 27 Oct 2020 01:06:10 GMT</pubDate><description>&lt;p&gt;How to perform full end-to-end entity linking has always been a challenging problem in NLP. The typical approach for this is to use a model to detect entities and then employ another model to perform entity disambiguation. And this paper beautifully formulates these two steps into a single neural network model. Paper https://arxiv.org/abs/2010.02413 Code https://github.com/facebookresearch/BLINK/tree/master/elq&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2010.02413/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.CL</category></item></channel></rss>
