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Ensemble Learning for Entity Linking by renatosjoao is a document available to read on EtoBox.

What is Ensemble Learning for Entity Linking about?

This document proposes an ensemble entity linking approach called MetaEL that combines the outputs of multiple existing entity linking systems. MetaEL uses supervised classifiers trained on features derived from entity mentions, documents, and surface forms to predict the best-performing entity linking system for each mention. It is presented in two variations - MetaEL+ LOOSE, which focuses on high recall by assigning entities from any predicted system, and MetaEL+ STRICT, which focuses on high precision by

Author

renatosjoao

Language

EN