Entity Linking: Finding Extracted Entities in a Knowledge Base
Theory and applications of natural language processingPublished 12 July 2012
Delip Rao, Paul McNamee, Mark Dredze
Citations181
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TL;DR
This work discusses the key challenges present in this task and presents a high-performing system that links entities using max-margin ranking and summarizes recent work in this area and describes several open research problems.
Abstract
In the menagerie of tasks for information extraction, entity linking is a new beast that has drawn a lot of attention from NLP practitioners and researchers recently. Entity Linking, also referred to as record linkage or entity resolution, involves aligning a textual mention of a named-entity to an appropriate entry in a knowledge base, which may or may not contain the entity. This has manifold applications ranging from linking patient health records to maintaining personal credit files, prevention of identity crimes, and supporting law enforcement. We discuss the key challenges present in this task and we present a high-performing system that links entities using max-margin ranking. We also summarize recent work in this area and describe several open research problems.
Keywords
Computer ScienceDecision SciencesBiochemistry, Genetics and Molecular Biology
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