Given a query consisting of a mention (name string) and a background document, entity
disambiguation calls for linking the mention to an entity from reference knowledge base like …

Abstract Biomedical Entity Linking (BM-EL) task, which aims to match biomedical mentions
in articles to entities in a certain knowledge base (eg, the Unified Medical Language …

Entity Linking aims to link entity mentions in texts to knowledge bases, and neural models
have achieved recent success in this task. However, most existing methods rely on local …

Abstract Most successful Entity Linking (EL) methods aim to link mentions to their referent
entities in a structured Knowledge Base (KB) by comparing their respective contexts, often …

Entity Disambiguation aims to link mentions of ambiguous entities to a knowledge base (eg,
Wikipedia). Modeling topical coherence is crucial for this task based on the assumption that …

In this paper we give an overview of the Tri-lingual Entity Discovery and Linking task at the
Knowledge Base Population (KBP) track at TAC2015. In this year we introduced a new end …

In this paper we give an overview of the Entity Discovery and Linking tasks at the Knowledge
Base Population track at TAC 2014. In this year we introduced a new end-to-end English …

Abstract Background The Entity Linking (EL) task links entity mentions from an unstructured
document to entities in a knowledge base. Although this problem is well-studied in news and …

Abstract Language identification, as the task of determining the language a given text is
written in, has progressed substantially in recent decades. However, three main issues …

Wikification for tweets aims to automatically identify each concept mention in a tweet and link
it to a concept referent in a knowledge base (eg, Wikipedia). Due to the shortness of a tweet …