We present mGENRE, a sequence-to-sequence system for the Multilingual Entity Linking
(MEL) problem—the task of resolving language-specific mentions to a multilingual …

This survey presents a comprehensive description of recent neural entity linking (EL)
systems developed since 2015 as a result of the “deep learning revolution” in natural …

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 …

In this paper, we study a novel approach for named entity recognition (NER) and mention
detection in natural language processing. Instead of treating NER as a sequence labelling …

A major challenge in Entity Linking (EL) is making effective use of contextual information to
disambiguate mentions to Wikipedia that might refer to different entities in different contexts …

Cross-lingual Wikification is the task of grounding mentions written in non-English
documents to entries in the English Wikipedia. This task involves the problem of comparing …

This paper presents DWIE, the 'Deutsche Welle corpus for Information Extraction', a newly
created multi-task dataset that combines four main Information Extraction (IE) annotation …

Generative approaches have been recently shown to be effective for both Entity
Disambiguation and Entity Linking (ie, joint mention detection and disambiguation) …

This paper introduces a subtask of entity linking, called character identification, that maps
mentions in multiparty conversation to their referent characters. Transcripts of TV shows are …