Joint Learning of the Embedding of Words and Entities for Named Entity Disambiguation

Understand

Named Entity Disambiguation (NED) refers to the task of resolving multiple named entity mentions in a document to their correct references in a knowledge base (KB) (e.g., Wikipedia).

• In this paper, we propose a novel embedding method specifically designed for NED.
• The proposed method jointly maps words and entities into the same continuous vector space.
• We extend the skip-gram model by using two models.